We are looking for a driven and highly analytical Senior Data Scientist.
Are you interested in utilizing machine learning and deep learning to develop new technology? Do you think in series of algorithms? Are you passionate about finding insights in data and using quantitative analysis to answer complex questions? If yes, then we would be extremely interested in speaking with you!
As part of the Data Science team, you will be working closely with the Analytics & Operations teams to develop proprietary models from structured and unstructured healthcare data.
The right candidate will need to operate independently and flexibly, identifying opportunities for insightful analytics and responding rapidly to ad hoc requests. Logical, linear thinking, and an ability to communicate rationale for analysis and defense of results will be important.
Who are we?
We support some of the world’s largest funds as an outsourced analytics and solutions provider in the life settlements space. The company is highly entrepreneurial, consistently evaluating different industries and markets for opportunities.
- Execute projects end-to-end, starting with problem formulation, solution architecture, as well as product implementation and integration
- Gather open source and third-party data sources to engineer relevant features for modeling
- Research, develop and implement the company’s core statistical and machine learning models to conduct predictive and prescriptive modeling
- 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
- Apply advanced mathematical 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, Applied Math or related field required
- A minimum of 7 years’ experience in a technical role, including a minimum of 5 years in a data science
- Strong fundamentals in problem solving, algorithm design and model building
- Advanced knowledge of building a variety of classification and clustering algorithms in Python and/or R
- Experience with Time Series Modeling highly desired (Recurrent Neural Networks, Markov Models,
Survival Analysis etc.)
- Proficiency training large scale models in, at least, one modern deep learning engine (Tensorflow, Keras, PyTorch, etc.)
- Experience with modeling Unstructured Data through NLP techniques (topic modeling, word embeddings)
- Experience working with healthcare data a plus
- Comfortable with extracting data and from XML and SQL
- Strong presentation and communication skills