Deloitte Services LP seeks a Lead Data Scientist in Boston, MA.
Work You’ll Do
Contribute to project research, including processing data, learning the sequence of analytic procedures, and developing an understanding of the overall intention of each project. Participate in team/project meetings to learn about project status, client requests, and manager demands. Adjust code/formulas/models to enhance the procedure of current projects. Leverage expertise in R/Python/SQL to process and model data and Tableau to deliver analysis insights for developing new procedures, new analytic processes, and new models to support new client requests. Build ad-hoc analysis to support quick client demands.
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Requirements
- Bachelor's (or higher) degree in Economics, Statistics, Mathematics, Finance, or related field (willing to accept foreign education equivalent).
- One year of experience performing statistical analyses for predictive modeling.
- Experience must include one year of:
- Analyzing complex data to develop solutions and reports that highlight gaps and other business information for the client;
- Performing validation of data;
- Performing advanced analytical assessments, remediation, and transformation of data for end-to-end solutions implementation;
- Performing model design and metrics and translating analytics into business specific requirements;
- Identifying data tables and relationship mappings to build analysis reports using advanced analytical tools, including R, Python, SQL, and Spark;
- Utilizing Tableau, Excel, and PowerPoint to deliver insights to leaders;
- Utilizing data sources, including firm P&L line items, headcount movements, recruiting records, opportunity data, backlog & pricing data, and econometrics variables, to provide in-depth data to the data science team and project leadership;
- Implementing built-in model feedback loops for data quality, model accuracy, model back-test, important predictors, and model outliers, to track and improve model performance;
- Identifying model features and validating model forecasting to provide updates on critical path milestones, progress, and risks; and
- Supporting deliverables and discussion points for senior-level internal firm leadership.
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