What you'll do :

• Actively engage with internal business teams to understand their challenges and deliver robust, data driven solutions.
• Work alongside global counterparts to solve data-intensive problems using standard analytical frameworks and tools.
• Be encouraged and expected to innovate and be creative in your data analysis, problem solving and presentation of solutions.
• Network and collaborate with a broad range of internal business units to define and deliver joint solutions.
• Work alongside customers to leverage cutting edge technology (machine learning, streaming analytics and ‘real’ big data) to creatively solve problems and disrupt existing business models.
• 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.

What makes you a great fit :

• 6+ 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