Cofounded by Dr. Dimitris Bertsimas of MIT, Benefits Science Technologies is a data science and technology firm innovating at the intersection of analytics, healthcare and software development. We are building THE data science-driven engine to help clients manage risk related to health care and insurance - empowering them to make optimal decisions to control costs and improve quality of care for their members. Our passion is finding unique answers to complex questions and continually re-defining the leading edge.
Under the direction of Chief Scientist Bertsimas and our Chief Strategy Officer, the Data Science Lead is responsible for leading our team of Data Scientists in all aspects of the design and implementation of Benefits Science’ world-class data analytics services and products. The Data Science Lead ensures exceptionally high standards and contributes to efficient operation within an interdisciplinary team focused on creating new client solutions. This is a full time, salaried position, with salary commensurate with education, experience, and contribution.
Duties & Responsibilities:
Lead and manage our Data Science team to the highest standards
Conceive, plan, and prioritize data projects, ensuring data quality and integrity throughout the process as well as alignment with organizational goals
Lead efforts in implementation of new machine learning and optimization methodologies as needed for specific models or analysis
Build analytic systems and predictive models to elevate customer experience, and track impact over time
Design, implement, and validate solutions in distributed environments
Research and experiment with new data science technologies and models, discover opportunities for new data analytics features, and influence product and technology development
Write high-quality, reusable and production ready code
Interpret and analyze data problems
Test performance of data-driven products
Collaborate with colleagues from engineering and business backgrounds; leading, supervising, and working as part of a team.
Must pass initial and periodic background checks, and comply with all applicable HIPAA and Security regulations, including maintaining HIPAA Awareness and Security Certification
Must be available and able to work during standard business hours in the Benefits Science office in Boston, MA, as well as at other times as needed
Ph.D. or MS in Operations Research, Statistics, Applied Mathematics, Industrial Engineering, Computer Science or a related field
If MS, then a minimum of 5 years relevant work experience applying Data and/or Statistical Analysis, Machine Learning, Mathematical Modeling, and Optimization (preferably Robust and/or Mixed Integer) to maximizing outcome or identifying best practices, preferably in the insurance/healthcare/health services sector, is required
If Ph.D. then a minimum of 2 years relevant work experience as outlined above and a B grade or above in the following courses is required: Design of Experiments, Machine Learning, Data Analysis.
Strong organizational and leadership skills and a business mindset, with leadership and management experience strongly preferred
Solid understanding of relevant theories in probability theory, statistics, machine learning, data structure and algorithms, optimization (linear programming, mixed-integer programming), etc.
Knowledge of data management and visualization techniques, as well as statistical analysis and predictive modeling
Experience testing algorithms and creating mixed integer optimization models to meet identified needs
Proficient in using Python to implement machine learning models and algorithms
Expert in data analysis using R or Python, with a preference for Julia also
Ability to initiate and drive projects to completion with minimal guidance
Experience moving developed models into a production environment
Fluent in building/prototyping machine learning models and algorithms and wrangling large datasets
Git or other collaborative version control
Experience with Big Data tools such as AWS, Hadoop, Spark
Knowledge of implementing mixed integer optimization models in Python, and experience working with commercial optimizers like Gurobi
Ability to work effectively as part of a team, with excellent interpersonal and communication skills
Fluent in English (both verbal and written)
Experience with Modern Deep Learning tools such as SQL, PySpark, TensorFlow, and Keras, and simulation tools such as Arena preferred
Additional Salary Information: Salary commensurate with education, experience, and contribution. Experience requirement may be waived for an exceptional PhD applicant.