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Data Scientist- Revenue Management

Position Summary: The Data Scientist, Revenue Management is responsible for support the development of all decision support tools/models used by revenue management team and for executing them efficiently. This employee will also perform regular statistical analysis and present results to senior leadership in a business format to assist in decision making and analysis. Essential Duties and Responsibilities: Design and develop models and algorithms that drive performance and provide insights, from prototyping to production deployment, across key areas of interest (e.g., APD optimization, Load Factor optimization, Cabin mix, channel mix) Design rich data visualizations to communicate complex ideas to internal and external teams. Execute various components of Data Science Life cycle: Data Wrangling, Feature Engineering, Data Visualization (discovery), Model Generation, Implementation and Maintenance. Collaborate with other analytical teams in the company and IT to design, and implement analytical projects Continuously seek out opportunities to further develop our analytical, engineering, statistical, etc. toolkit & team Qualifications: Bachelor’s degree from four-year College or university required (in Operations Research, Industrial Engineering, Statistics, Management Science or related field). Candidate shall have demonstrated 1 to 3 years of (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical analysis techniques typical to exploratory data analysis. Equivalent combination of education and experience will be considered. Strong problem solver and natural curiosity to learn Candidate shall possess the necessary skills to write scripts in R or Python to conduct exploratory and advanced statistical analyses Candidate shall possess the skills necessary to clean and wrangle data Candidates shall possess the skills necessary to extract data from data warehouses. Candidate shall possess excellent oral and written communication skills with emphasis on complex technical and statistical topics and effectively communicating details with all levels of management Ability to contribute in multiple projects simultaneously with deadlines and manage changing priorities with minimal supervision and intervention

/ Miami, United States

Junior Business Analyst

Client: CONFIDENTIAL Title: Junior Business Analyst Location: New York, NY Type: Contract to Perm Salary: Based on Experience Here are some of the qualifications we are looking for. Functions: Creating detailed requirements documents using the appropriate templates and/or analysis tools. Performing 1st and 2nd level support for the CRM SalesForce, SalesForce Marketing Cloud, Wave Reporting, and Forms Tool systems. Following up regularly with the user community to identify system issues and requirements. Working with business unit personnel to prioritize work accordingly. Meeting with developers to review system requirements Testing systems and enhancements before presenting to the user community Conducting user acceptance testing when implementing functionality, bug fixes, or new systems Handling multiple analyst assignments concurrently Preparing user training documentation & performing one-on-one or group training sessions with users Experience and Skills 3-5 years experience in a professional business environment/providing system support Bachelor’s degree in Information Technology preferred but not required Salesforce Marketing Cloud experience preferred Demonstrated self-starter who can complete projects with minimal supervision Strong written and verbal communication skills -Ability to write a complete, detailed requirements document that describes a significant enhancement or new system area -The ability to communicate effectively via email with business users, team members, and other IT groups Ability to interact well with business users at different levels within the organization Excellent at setting user expectations regarding general system support as well as for enhancements & bug fixes Keen prioritization skills and the ability to handle multiple tasks or projects concurrently Ability to work well in a collaborative, team-oriented environment Ability to work in a high-pressure environment and meet critical deadlines

Contract / Manhattan, United States

QA Manager

Responsibilities: Manage a multifunctional team of manual and automation QA Engineers responsible for web and mobile applications and the data platform supporting them. Define quality procedures, always putting the end user experience foremost Define the tools and scope for automated testing Develop performance testing approach for data platforms and web/mobile applications Ensure test strategy and procedures are properly created, understood, carried out, and evaluated Align, communicate, and socialize department vision and goals Manage and create resourcing plans, reports, and expectations around product quality Communicate project status and escalate issues to engineering and architecture leads Work closely with product teams to define and achieve sprint goals Coach, mentor and enable QA Engineers Qualifications: Strong sense of team ownership and accountability, strong ability to prioritize Knowledge of how to position QA as a service Skill and familiarity testing tools and bug/test case management software Working knowledge of processes, and principles for web/mobile applications and data platforms Experience testing ETL processes and ensuring data quality is a must Experience with AWS solutions is a plus 4+ years QA management experience Proven track record that shows personal career growth Experience in JIRA, Confluence, Jenkins, etc is a plus Agile experience is a must

/ New York City, United States

Big Data Developer

Big Data developer requirements: We are looking for Big Data developer with strong expertise in Spark, Scala and PySpark. Experience with Hadoop configuration and maintenance is a plus. Solid experience of Hive, Sqoop, Hadoop and ETL processes. Ability to lead, guide and mentor junior developers. Required Skills: • Strong expertise in Apache Spark using Scala and PySpark is mandatory • Experience in Hive, Sqoop, noSQL databases are required • Strong SQL, Python and shell scripting • Working with Apache Kafka expertise is required • Working experience in Oracle, SQL Server and other major databases • Hadoop Admin is a plus Required Experience: • Spark: 4 years (Preferred) • Scala: 4 years (Preferred) • Big Data: 5 year (Preferred) • Software Development: 9 years (Preferred) • Hadoop Admin using Hortonworks, Claudera or MAPR is plus

Contract / Coral Gables, United States

Senior ETL Informatica Developer

Job Summary: Work with multiple data warehouse efforts with minimal supervision. Gather, analyze and understand business requirements. Develop, validate and implement efficient ETL code for data integration layers (data warehouse or data marts) to deliver multiple projects. Optimize the data environment for efficient data access and monitor performance of data warehouse ETL processes to ensure service level agreements with our users are met and implement tuning as needed. Manage the ETL processes and Informatica environments. Follow best practice, guidelines/procedures and naming conventions with enterprise-wide data collection and extraction. Work closely with database administrators and Unix engineers with database and infrastructure installations, designs and maintenance. Provide production support for all ETL processes. Plan and support lifecycle of data warehousing infrastructure components including database, operating system, ETL tools and various vendor products. Maintain and manage technical meta data and documentation for data warehousing and ETL processes. Serve as subject matter expert on assigned projects, production support areas and knowledge transfer to other team members. Essential Job Functions: 1. Be responsible for translating business needs into technical solutions and specifications, and designing relational and/or dimensional models or flat files to meet project requirements. Perform source system data profiling including structure, data and relationship discovery; be responsible for understanding source system database structures and underlying data and knowledge transfer expertise to DW team members 2. Develop, manage and update conceptual, logical, and physical data models; evolve existing models to meet new and changing business requirements 3. Design, develop, maintain, test and modify ETL (Extraction, Transformation and Loading) processes with efficiency, best practices, naming conventions and ease of maintenance in mind; ensure quality and accuracy of the delivered data; ensure SLA (Service Level Agreement) with clients are met 4. Document ETL technical design process, high level and detailed meta data and reconciliation process; update DW production Informatica and Big Data job schedule document and document production issues and resolutions within On Call Tips 5. Provide production support for all existing DW applications; respond to job failure related text page and/or emails in timely manner for critical DW applications 6. Scope, plan, prioritize and manage multiple tasks and projects; improve efficiency by working on other assigned tasks/projects while waiting for information on certain project(s) 7. Determine approaches to solutions, troubleshoot and maintain ETL processes with minimal guidance from team leads and supervisor 8. Follow project methodology of DW full development life cycles, prepare estimate and duration for development tasks and activities; provide bi-weekly project status to management on time; adhere to ETL development/migration standards by following ETL code review process on SharePoint and change control policies and procedures by submitting required documents in System Center for Service Manager (SCSM) 9. Plan and support lifecycle of DW infrastructure components including database, operating system, ETL tool and other vendor products with guidance from team leads and supervisor; participate in migrations and upgrades; monitor performance of ETL processes and implement tuning as needed with guidance from team leads 10. Maintain a positive work environment by acting and communicating in a manner which facilitates the success of business operations in order to meet company demands and expectations

Contract / Coral Gables, United States

CRM Business Analyst (Salesforce)

Client: CONFIDENTIAL Title: CRM Business Analyst (Salesforce) Location: New York, NY Type: Contract to Perm Salary: Based on Experience Here are some of the qualifications we are looking for. Functions: Creating detailed requirements documents using the appropriate templates and/or analysis tools. Performing 1st and 2nd level support for the CRM SalesForce, SalesForce Marketing Cloud, Wave Reporting, and Forms Tool systems. Following up regularly with the user community to identify system issues and requirements. Working with business unit personnel to prioritize work accordingly. Meeting with developers to review system requirements Testing systems and enhancements before presenting to the user community Conducting user acceptance testing when implementing functionality, bug fixes, or new systems Handling multiple analyst assignments concurrently Preparing user training documentation & performing one-on-one or group training sessions with users Experience and Skills 3-5 years experience in a professional business environment/providing system support Bachelor’s degree in Information Technology preferred but not required Salesforce Marketing Cloud experience preferred Demonstrated self-starter who can complete projects with minimal supervision Strong written and verbal communication skills -Ability to write a complete, detailed requirements document that describes a significant enhancement or new system area -The ability to communicate effectively via email with business users, team members, and other IT groups Ability to interact well with business users at different levels within the organization Excellent at setting user expectations regarding general system support as well as for enhancements & bug fixes Keen prioritization skills and the ability to handle multiple tasks or projects concurrently Ability to work well in a collaborative, team-oriented environment Ability to work in a high-pressure environment and meet critical deadlines

/ Manhattan, United States

Quality Assurance Engineer

Responsibilities As QA Engineer you will work with Product Managers, Developers and Delivery Leads to assist with website and mobile app testing across Sony Music Data Analytics properties. Execute test cases for integration, functional and regression testing in a fast paced environment Test integrations with third party software and platforms Report and track software defects in Jira Analyze test results and make recommendations Assist in testing post production releases Qualifications 2+ years of software testing experience Knowledgeable in QA methodologies and best practices Test automation software such as Selenium a plus Experience testing web and mobile applications Experience with defect tracking tools Works well in an Agile and dynamic environment Good written and verbal communication skills

Contract / Miami, United States

Risk Analytics Modeling Specialist

The Risk Analytics Modeling Specialist participates in performing effective Model Risk Management of bank-wide models, through every aspect of the model life cycle, from model development, implementation and use, to a rigorous model validation, including specific governance and controls, in order to comply with Amerant Bank’s Model Risk Management Policy and regulatory guidance. Will also be responsible for collaborating in developing quantitative analysis/models for the Risk departments. Duties and responsibilities include: Perform, with manager guidance, periodic independent model validation, including evaluation of conceptual soundness, data quality & integrity, syntax validation, and model performance, in accordance with internal policy and regulatory guidelines to ensure ongoing model effectiveness. Review the underlying assumptions, theory, derivation, empirical evidence, implementation, limitations, governance and controls of the model being validated. Perform back-testing, model bench-marking, and sensitivity analysis of the model being validated. Develop challenger models and methodologies with their appropriate documentation to identify improvements. Prepare validation report and communicate results of the validation to the model owner, as well as, prepare the presentation for Senior Management Committees and the action plan for the model being validated Work closely with the model owners/users (business, Market Risk, Credit Risk, Finance, BSA, Fraud Prevention, among others) to understand model details and to develop and implement recommendations. Collaborate with the unit to ensure compliance of model development standards and procedures with regulatory requirements, as well as, ensure a correct model implementation and use. Participate in the training plan for the Risk Analytics team to ensure appropriate and effective use of the analytical tools and new techniques in accordance with their intended objectives. Participate in the development of reports and special assignments. Follow-up action plans to ensure findings/recommendations are completed on time and satisfactory. Educational Background: Bachelor’s Degree (masters preferred) in statistics, mathematics, finance, risk, engineering, or related discipline. Work Experience: Minimum three years of work experience is required in quantitative modelling and/or developing Risk Management Models and/or performing Model Validation at Financial Institutions or companies servicing Financial Institutions. Technical Skills & Requirements: Exhibit excellent mathematical, statistical and analytical skills; exposure to quantitative analysis and risk management; and knowledge of predictive modeling, segmentation and simulation techniques; use of statistical tools (SAS); data bases (SQL); and advanced use of Excel and PowerPoint. Extracting, Structuring information from Databases (SQL). SAS programmer is strongly preferred. Knowledge and experience with various models -- Credit Risk, Market Risk, Operational Risk, PPNR, and analysis tools including SAS and Excel applications preferred. For more information and to apply online, please visit our careers page at https://amerantbank.com/careers Seniority Level Associate Industry Financial Services Employment Type Full-time Job Functions Accounting/Auditing Analyst Information Technology How you match Criteria provided by job poster Skills Match Analytics No match Mathematics No match Financial Institutions No match SQL No match Risk Management No match Microsoft Excel No match Analytical Skills No match Risk Analytics No match Model Validation No match Modeling Level of education Match Bachelor's Degree

/ Coral Gables, United States

Fraud Data Analytics Officer

The Fraud Data Analytics Officer must be able to analyze transaction patterns and fraud trends to develop effective and dynamic anti-fraud strategies based on fraud types and customer segments. Will also manage rule life cycle including performance analysis and reporting. Responsibilities Include Examine past and current fraud trends, running data reports and analyzing results in order to implement effective fraud mitigation strategies. Responsible for applying validation processes to fraud rules. Perform trend analytics using valid transaction and fraud data to identify patterns and make recommendation for improved controls. Responsible for creation statistical reporting based upon a large volume of data and identify fraud trends based on specific transaction attributes and historical transaction data. Identify, analyze and resolve complex issues with limited supervision using various fraud tools, applications and systems. Develop, implement and improve comprehensive fraud detection strategies and authorization decision rules that balance fraud loss reduction, costs and customer experience. Designs experiments, test hypotheses, and build models. Conducts advanced data analysis and highly complex designs algorithm. Applies advanced statistical and predictive modeling techniques to build, maintain, and improve fraud reduction controls. Leads discovery processes with stakeholders to identify the business requirements and the expected outcome always aligned with the reduction of fraud. Models and frames scenarios that are meaningful in the fraud reduction arena. Provides on-going tracking and monitoring of performance of the rules behaviors and fraud models. Leads the design and deployment of enhancements and fixes to the fraud model as needed. Prepare monthly, quarterly and annual reports as it relates to changes made to strategies, their impact & performance indicator results. Ongoing personal development and understanding of evolving analytical tools and technologies available that may be implemented to enhance work performance. Maintain open and ongoing collaboration and communication with front-line team; obtaining feedback and incorporating their day to day experiences into proposed solutions to mitigate negative impact to customers. Work with product owners and business functional areas in developing fraud prevention initiatives for plastics that balance risk and customer service. To identify, evaluate, monitor and make any recommendation deemed necessary to their respective Risk Management Committee in order to assess, reduce, eliminate or control any current or prospective risks to earnings or capital arising from violations of, or nonconformance with, laws, rules regulations, prescribed practices, internal policies and procedures or ethical standards. Maintain knowledge of bank fraud trends and card association rule and regulations. Minimum Work Experience Requirements: Minimum five years experience in the financial industry working in the fraud prevention arena. Proven analytic experience and capability preferably in risk related products and risk strategies. Knowledge of MasterCard & Visa Risk Management Policies & Procedures preferable. Minimum Education And/or Certifications Requirements: Bachelor's Degree in Business/MIS/Quantitative areas such as Mathematics or Statistics, or equivalent combination of education, related course work and hands-on experience with risk analytics systems. Technical And/or Other Essential Knowledge: Proficiency in SAS and SQL programming, Excel and Access. Predictive modeling experience. Strong background in statistics and mathematical optimization, forecasting and simulation. Strong analytical and problem solving skills. Ability to analyze fraud trends and recommend effective mitigation strategies. In addition to advanced analytic skills, this role is also proficient at integrating and preparing large, varied datasets, architecting specialized database and computing environments, and communicating results. Make sound decisions based on precedent, data analytics, judgement and experience. Working knowledge of data analysis software and tools. Knowledge of relational databases.

/ Coral Gables, United States

AEM Developer

MicroStrategy transforms organizations into intelligent enterprises through data-driven innovation. We match smart people to dynamic projects and technologies that truly challenge their talents. Curious and creative in outlook, our success is built on the talent and energy of smart and driven people. MicroStrategy (Nasdaq: MSTR) is a worldwide leader in enterprise analytics and mobility software. A pioneer in the BI and analytics space, MicroStrategy delivers innovative software that empowers people to make better decisions and transform the way they do business. We provide our enterprise customers with world-class software and expert services so they can deploy unique intelligence applications. Job Description The Role: MicroStrategy is looking for mid to senior level Java/JSP developer with a background in developing web applications in Adobe Experience Manager (AEM). This person will collaborate closely with our marketing, user experience, design and web development teams. Your Focus Work in a collaborative team environment to design and develop solutions for MicroStrategy’s corporate website Collaborate with AEM implementation vender to conduct regular design and code review sessions Partner with Visual Design and User Experience teams to develop effective/engaging designs Translate business goals into technical requirements, prepare the technical design solutions and implement these solutions throughout the project lifecycle Support day-to-day operational tasks and assist in ensuring the quality of company website

/ Tysons Corner, United States

Senior Machine Learning Engineer

Raymond James is looking for a Senior Machine Learning Engineer to join its Data Science team. This individual will be responsible for architecting, designing and building enterprise-scale machine learning applications as a core service. This will include taking models developed by data scientists and integrating it in with the rest of the company’s platform. The goal will be to bring machine learning and optimization models into production together with a highly multi-disciplinary team of data scientists, data engineers, business analysts, strategic partners, product managers and domain experts. This is a new role within the organization, so the desire and ability to quickly ramp up and grow into a technical lead as we continue to build out the team will be crucial for long term success. Responsibilities: Partners with data scientists, data engineers, analysts, subject matter experts and business stakeholders to operationalize models and deliver insights to the business. Architects platforms which are highly modular, scalable, and responsive; and that serve as a foundation for building key enterprise Data Science components. Ensures that the Machine Learning code, models and pipelines are deployed successfully into production, and troubleshoots issues that arise. Automates model training and testing and deployment via machine learning continuous delivery pipelines. Builds data APIs and data delivery services that support critical operational and analytical applications for internal business operations, customers and partners Involved in all aspects of SDLC process from requirements, design, and build through deployment. Translates business requirements into working foundational components for platform thus ensuring functional and non-functional aspects are met. Defines strategic direction and develops tactical plans. Works with application and infrastructure teams to provision platform components. Effectively identifies opportunities for change, implements change and introduces new concepts, procedures, policies and tools while providing a clear explanation of benefits and purpose. Documenting architectural standards, best practices and mentoring application teams on developing highly distributed, resilient and responsive applications. Serves as the primary point of contact on the most complex or escalated issues and may provide direction and guidance to team members. Understands and incorporates best practices in security and data protection. Qualifications Minimum of a B.S/M.S. in Computer Science, Electrical Engineering or related degree and five to seven (5-7) years of related experience or a combination of education, training and experience. Seven to Ten (10) years of experience in architecting and building high performance enterprise scale applications strongly preferred. Experience with design patterns and implementation and deployment AI and/or data science products. Expertise in the use of a variety of classic and modern machine learning techniques including clustering, decision trees, classification, regression and neural networks/deep learning. Expertise in mining complex data (including structured and unstructured), identifying patterns, and feature engineering Experienced in using AI/ML platforms, technologies, techniques (e.g. TensorFlow, scikit-learn, Spark ML/MLlib, etc.) Highly experienced with back-end programming languages and associated frameworks (Python/Flask preferred). Proficient in the use of front-end programming languages (HTML, CSS, JavaScript) and familiarity with common javascript libraries (d3) and frameworks. Experience with distributed version control systems and tools (Github/Git) and with automating application deployment, continuous delivery, and continuous integration (Jenkins) Experienced with deploying and managing infrastructures based on Docker or Kubernetes, and cloud platforms such as Azure, AWS or Google Cloud Platform. Experience in designing, building, and deploying production-level data pipelines using tools from Hadoop stack (HDFS, Hive, Spark, HBase, Kafka) Knowledge of data engineering and experience with profiling and optimizing large scale data processing systems; Familiarity with Linux and scripting languages. Proficiency with SQL and NoSQL databases Experience implementing and integrating with RESTful API services (preferred) Licenses/Certifications: None required.

/ St. Petersburg, United States

Senior Architect, Platform Engineering

Senior Architect, Platform Engineering As the Senior Architect on the Platform team, you’ll be creating tools, processes, automation and scripting that will support our product teams in building and delivering high quality features faster, more reliably while minimizing coordination with other product teams. In this position, you’ll be collaborating with other Senior Architects and product owners that represent different product groups to define and build tools, libraries, deployment scripts and CLI’s that increase each team’s productivity. Success in this position will allow the individual product teams to focus on building features without worrying about the underlying infrastructure. You will also participate in identifying and building shared services that enable the self-service usage of product teams. This includes data API’s as well as developer tools that will increase the productivity of the entire organization. Qualifications: Experience architecting solutions that incorporate common methods and approaches for common, cross-cutting concerns (logging, security, monitoring, data access etc) Must thoroughly understand automated testing concepts and frameworks Knowledge of best practices in designing and running GraphQL servers in production Hands-on experience in correctly writing and maintaining unit, integration, end-to-end and snap-shot tests on both client and server code Experience building CI/CD pipelines that incorporate the entire development lifecycle Establish common boilerplates, patterns and practices across teams to improve consistency and interoperability Experience in the Apollo Platform for building GraphQL servers and clients Comfortable functioning as a subject-matter expert in DevOps and cloud computing as it relates to CI/CD pipelines Active contributor to one or more open source projects Comfortable working in terminal shell scripting Requirements: 3+ years of experience building CI/CD pipelines which incorporate the dev, test, deploy lifecycle seamlessly 5+ years working in scripting and automation frameworks across multiple platforms 5+ years designing, deploying, and supporting production cloud environment in the AWS ecosystem 3+ years of experience building reusable libraries in Javascript and deploying them to NPM 5+ years of experience building, deploying and operating cloud-native applications in AWS or other cloud providers Significant experience in at least 2 of the following technologies: MongoDB, NodeJS, GraphQL, Java, Adobe Experience Manager, Jenkins / BitBucket Pipelines, Apollo Platform

/ Miami, United States

Lead Data Scientist

Position Summary: Spearheads the analysis and examination of the business to define needs and/or opportunities; leading the gathering, and analysis of data and formulating a recommended course of action. The primary area of focus is leveraging existing Data Science initiatives or deploying new models or AI technologies. This role is responsible for seeing projects through from start to finish while leading a team of analysts and managing resources across the technical divide. Has responsibility for all areas within the global contact centers to define metrics that will assist the business with goals as set forth by organization leaders in a global context. Understands, analyzes and documents data to deliver informative, well-organized presentations to senior and executive management regarding processed forms i.e. guest satisfaction, enrollments, guest demographics, employee satisfaction, etc. Leads the development of functional and system specifications. Essential Duties and Responsibilities: Develop and maintain demand forecasting model (time series, regression, segmentation models etc.) Use non-linear regression models to develop price elasticity models Knowledge of linear and integer optimizations Knowledge of Machine Learning, Deep Learning, Neural Networks Knowledge of Voice Analytics and Text Mining Manage the relationship with other analytical teams in the company and IT to design, and implement analytical projects Project management experience to identify business needs, translate business needs into technical requirements, and implement analytical models to meet project deadlines. Perform algorithmic modeling contact center workforce management and work closely with the OCU and finance teams. Integrate with external data sources to discover interesting trends. Design rich data visualizations to communicate complex ideas to internal and external teams. Design and manage data QA and validation using automation and best practices. Collaborate directly with teams/individuals across the company to facilitate the design, research, development, and delivery of data statistics, models and client deliverables. Take ownership of the various components of Data Science Life cycle: Data Wrangling, Feature Engineering, Data Visualization (discovery), Model Generation, Implementation and Maintenance. Continuously get better - seek out opportunities to further develop our analytical, engineering, statistical, etc. toolkit Respond to ad-hoc data and analysis needs while supporting various projects. Conduct analyses of business data, evaluate trends and pattern changes, and learn to disperse results in a format appropriate for the audience. Financial Responsibilities Support reporting, systems and modeling of current and expected revenue & bookings to support daily and strategic decisions and analyses. Qualifications: Master’s degree in Operations Research, Industrial Engineering, Statistics or Management Science is preferred. Bachelor’s degree from four-year College or university required (in Operations Research, Industrial Engineering, Statistics, Management Science or related field). Post-grad experience as a Data Scientist, preferably 3+ years of experience, including experience designing statistical models. Equivalent combination of education and experience will be considered. Demonstrated experience with AI technologies such as speech analytics, sentiment analysis, chatbots, etc. Knowledge and Skills: Database and analytical programming skills (including SAS or R, SQL, Python, etc.) Experience with text analytics and artificial intelligence models Ability to assimilate ideas/concepts into data driven models and strategies. Strong Operations Research modeling skills (optimization and linear programming, etc.). Statistical modeling skills (regression and forecasting, etc.) Advanced Excel skills Ability to present information to executive management, internal and external customers Ability to work with mathematical concepts such as probability and statistical inference. Ability to apply concepts such as fractions, percentages, ratios and proportions to practical situations. Ability to define problems, collect data, establish facts and draw valid conclusions. Ability to interpret an extensive variety of technical instructions in mathematical or diagram form. Ability to collect, analyze, and interpret revenue performance data Ability to structure logically quantitative analysis of complex issues Project management experience in organizing, planning and executing large-scale projects from conception through implementation. Effective verbal and written communication skills. Understanding of the business in order to validate findings and conclusions and ensure data integrity and accuracy at all times. Understanding of database design and information systems, structure, functions and processes, and experience with database tools. Ability to work in a fast-paced environment while managing multiple projects and responsibilities at once Expertise in data visualization

/ San Francisco, United States

Knowledge Graph Developer

Essential Duties and Responsibilities: A successful candidate will have hands-on experience with graph database and web applications and the desire to work in a high performing and faced-paced team. Excellent analytical and problem-solving skills are a must as well as a track record of taking complex concepts and implementing practical solutions. Major responsibilities include: Lead the design, development, testing, and deployment of a graph database solution. Design and develop graph data models in accordance with leading practices for our use cases. Work with system owners and data engineers to identify and integrate with data sources used to hydrate the knowledge graph. Create and manage queries to pull insights from the knowledge graph. Optimize for high performance, efficiency, scalability, and stability of the database. Define the database architecture and development best practices. Assume the role of a trusted-advisor, offering technical insights to the team and business stakeholders. Qualifications: Basic Qualifications BS degree in Computer Science or related technical field, or equivalent practical experience. 4+ years of proven working experience as a software developer or data engineer. Strong track record of delivery using graph databases such as Neo4j, TitanDB or OrientDB. Fluency with graph query languages such as Gremlin, Cypher, SPARQL. Preferred Qualifications Experience in designing, creating and maintaining recommendation engines. Experience in Java / Scala development. Knowledge of a scripting language like Python or Ruby. Strong experience with RESTful API interfaces and microservice architectures. Knowledge of statistics and experience using statistical packages for analyzing large datasets (R, Excel, SPSS, SAS etc) Experience with Microsoft Azure or Amazon Web Services (AWS) Experience with Agile software development. Knowledge and Skills: The ideal candidate has: Experience in developing knowledge-based systems in different contexts such as information retrieval, intelligent agents, dialog systems and recommendation systems. Experience in scalability and performance issues concerning very large knowledge stores. Experience with information extraction through creation of an application layer. Experience developing REST / JSON applications and multi-threaded applications. Strong background in computer science: algorithms, data structures, concurrency, and distributed systems. Strong OO Programming and OO Design knowledge. Knowledge of professional software engineering practices & best practices for the full software development life cycle including coding standards, code reviews, source control management, build processes, testing, and operations. Technical expertise regarding data models, database design development, data mining and segmentation techniques. Technical capabilities with Cloud Services and Micro Services Patterns, API Management, Azure and AWS Services. Strong communication (verbal and written) and collaboration abilities in addition to technical depth. Comfortable delivering within an agile program.

/ Miami, United States