The Lead Data Scientist will utilize data science and machine learning to build algorithms and statistical models, optimize customer experiences and business outcomes, and manage multiple data science projects. Responsibilities include developing predictive models, constructing ETL pipelines, creating interactive dashboards, and providing technical leadership while collaborating with cross-functional teams.
Responsibilities
- Leverage data science and machine learning technology to build algorithms, statistical models and analytical solutions
- Use predictive modeling to increase and optimize customer experiences, revenue generation, data insights, and other business outcomes
- Build ETL pipelines in PySpark/Python that process transaction and account level data and standardize data fields across various data sources
- Organize and manage multiple data science projects with diverse cross-functional stakeholders
- Work alongside global counterparts to solve data-intensive problems using standard analytical frameworks and tools.
- Design & implement interactive dashboards and reports. Build visualizations of data model performance and results.
- Actively engage, network, collaborate with internal teams to deliver data driven solutions.
- Provide technical leadership in a team that generates business insights based on applied analytics. Identify actionable recommendations. Communicate the findings to business seniors.
Pre-Requisites for candidates
- 10+ years of work experience with a Bachelor’s Degree or 8+ years of work experience with an Advanced degree (e.g. MTech, MSc, MBA) or 7+ years of work experience with a PhD degree
- (Preferred) Master’s degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, Marketing Research.
- 8+ years of experience in data-based decision-making, quantitative analysis, & experience applying data science to solve problems such as new customer acquisition, attrition management and product mix models
- Expertise in the following activities: Large scale data mining, data cleansing, diagnostics, preparation for Modeling. Predictive modeling and machine learning. Multivariate techniques & predictive modeling – cluster analysis, discriminant analysis, CHAID, logistic & multiple regression analysis. Building data analytics models using Python, ML libraries, Jupyter/Anaconda. Exploring data & writing analytics algorithms in Python.
- Working knowledge of MS Azure Suite - Azure ML Studio, Azure Data Factory, Power BI/Power Apps
- Experience leading other data scientists in machine learning projects
- Strong verbal, writing & presentation skills
- Experienced in handling multi-national projects and team engagements
- (Preferred) Application of data analytics to manufacturing industries or chemical industries
Top Skills
Python
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