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As a Data Scientist Lead, you'll develop machine learning models, design data pipelines, and collaborate with cross-functional teams to enhance business outcomes.
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The Lead Data Scientist will define and execute AI/ML strategies, mentor a team, design ML/DL models, and ensure integration on Azure, driving measurable outcomes.
Top Skills:
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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
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Dubbed the "Silicon Valley of India," Bengaluru has emerged as the nation's leading hub for information technology and a go-to destination for startups. Home to tech giants like ISRO, Infosys, Wipro and HAL, the city attracts and cultivates a rich pool of tech talent, supported by numerous educational and research institutions including the Indian Institute of Science, Bangalore Institute of Technology, and the International Institute of Information Technology.
