Lead Data Scientist

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 Bachelors 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) Masters 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.