The Senior Data Scientist is instrumental in helping the business continue its evolution into an analytical and data-driven culture. The Senior Data Scientist synthesizes and leverages the company’s data and information assets to enhance business capabilities that will support company goals. This role supports relevant stakeholders through quantitative analytics and provides advanced expertise on data science concepts for the broader Corporate Analytics department. Considered a key leadership position within the company, this senior level role is expected to develop and drive the optimum analytic roadmap within various strategic areas.
- Provide expertise and leadership around adopting best in class processes and techniques for statistical analysis and modeling as well as the roll out of Big Data capabilities, consumer initiatives, and analytic deployment frameworks.
- Conduct research around the design, implementation, and validation of cutting-edge algorithms in order to analyze diverse data sources that will enable desired business outcomes in diverse fronts.
- Drive strategic thinking and the development of analytic roadmaps to support the goals within P&L centers.
- Collaborate with key functional areas to ensure continuity and advancement of analytic reporting and analysis.
- Interpret data, extract trends and created recommended action plans from data and statistical analysis.
- Leverage large proprietary and third-party datasets in novel ways to derive insights and optimize processes.
- Participate in the construction of research data suitable for statistical research, testing, and prediction.
- Provide mentorship and guidance to other team members while simultaneously guaranteeing statistical integrity, accuracy, and adequacy within the department.
- Provide recommendations and training for the data science tech stack and process for collaborative model development.
- Data Science Leadership
- Analytical and critical thinker with a high attention to detail and an ability to instill trust in key stakeholders around accuracy and overall relevance of work.
- Must understand how to communicate to a non-technical audience with skills that encourages participation and brings clarity to highly complex work.
- Demonstrated ability to creatively think outside of the box and look for new ideas around improving company performance and operational efficiency.
- Expert level ability to drive meetings and work with cross functional teams.
- Strong skills around execution and demonstrated ability to hit timelines.
- Fully independent decision-making skills that lead to minimal rework and trust within the organization.
- This position will be depended upon to drive the direction of analytic roadmaps that accomplish the following:
- Prioritizes the most meaningful analytic projects.
- Considers benefit, cost, and IT resources.
- Manages the progression of analytic and data development/maturity within a functional area.
- Technical, Data, and Reporting Skills
- 3+ years of experience with Python or R (Some Python experience is required).
- 3+ years of experience with SQL.
- 3+ years of experience using Jupyter notebooks or similar.
- Proficiency with Git and knowledge of Git Flow.
- Solid understanding around the intersection of Big data environments and analytics such as data lake construction, GCP/Azure applications, and cloud deployment.
- Expert level of ability to (a) work with large data containing complex transaction-based schemes, (b) handle challenging merge requirements to assemble data, and (c) apply appropriate cleansing techniques to make data suitable for advanced modeling exercises.
- Solid understanding of unstructured data such as text, photographs, video, and audio files.
- Demonstrated ability around translating requests and requirements into concise and useful reports.
- Expert level skills around data visualization setup and tools that can provide business leaders with the ability to deep dive relevant data.
- 3+ years with modern dashboarding software (Tableau, PowerBI, etc.).
- Statistical Modeling and Implementation
- Mastery of statistical techniques including regression (OLS, GLMs, logistic, Tree-Based Models) and other core multivariate techniques, deep learning techniques, machine learning algorithms, text mining / NLP, and A.I. concepts.
- Proven expertise in ML model tuning.
- Demonstrated success in building and deploying solutions that enhance the understanding and application of consumer churn, segmentation/profiles, lifetime value, trend detection, and product optimization to name a few.
- Demonstrated ability to support IT with Model Ops expertise. Must be comfortable working with IT teams to understand model requirements for data inputs and outputs.
- Experience standing up models in production as well as monitoring concepts necessary to alert problems with model performance and input/output changes.
- Understands how to translates business requirements into quick prototypes that enable more effective execution of data and analytics campaigns and the achievement of overall business targets/objectives.
- Proven experience with the complete model lifecycle, from requirements gathering to production.
Prior leadership experience is a plus. Expectations will be focused on intern management and the ability to lead high impact consulting services and other partnerships.
EDUCATION AND EXPERIENCE REQUIREMENTS
- Master’s degree in a quantitative field (computer science, physics, mathematics, statistics, engineering, bioinformatics, business or policy analysis, etc.) with an emphasis on predictive modeling.
- 7+ years of professional experience in an analytical role. No actuarial exams required.
- Property/casualty insurance background/experience are helpful, but not required