Senior Data Scientist

Senior Data Scientist

This is a director level position focused on supporting the business and analytical teams. The ideal candidate will have an extensive background in math and probabilities and advanced analysis expertise. A successful candidate will be passionate about finding insights in data and using quantitative analysis to answer complex questions, with a collaborative and resourceful style. The right candidate will need to operate independently and flexibly, identifying opportunities for insightful analytics and responding rapidly to ad hoc requests. The company supports some of the world’s largest funds as an outsourced analytics and solutions provider. They are highly entrepreneurial, consistently evaluating different industries and markets for opportunities. Logical, linear thinking, and an ability to communicate rationale for analysis and defense of results will be important.


  • Execute projects end-to-end, starting with problem formulation, solution architecture, as well as product implementation and integration
  • Research, develop and code the company’s core statistical and machine learning models to conduct predictive and prescriptive modeling on the company’s data and available and relevant third-party data
  • Integrate the outcomes as real time data products to elevate the company’s ability to provide enhanced pricing and forecasting for mortality-based assets and investments
  • Synthesize facts, theories, trends, influences and key issues and/or themes in complex and variable situations
  • Apply advanced math and statistical tools and programming languages to invent and evaluate algorithms/model designs to solve problems and guide business decisions
  • Evaluate tools and techniques that can raise the level of analytics at the company


  • Masters / PhD degree in Computer Science, Statistics or Applied Math or related field required
  • A minimum of 7 years’ experience in a technical role, including a minimum of 3 years in a data science role required
  • Strong programming background in SQL
  • Expert level knowledge of building algorithms in Python or R
  • Experience deploying statistical (Logistic Regression, Time Series/ Survival Analysis, Bayesian) and machine learning (Decision Trees, SVM, Clustering) algorithms
  • Interest in exploring and applying deep learning (CNN, RNN, GAN) to unstructured data
  • Strong presentation and communication skills
  • The following are considered pluses in an ideal candidate:
    • Previous experience presenting or lecturing to large groups
    • Experience working with large datasets using big data technologies (Spark, Hive, Hadoop)