Senior Data Scientist - Corporate Finance Domain

Profile: Sr. Data Scientist

Domain: Corporate Finance

Tools/Skills: Python, R, Data Analytics, Forecasting

Experience: 6+ years

Qualification: Master's degree in Computer Science, Statistics, Applied Mathematics, or related field.

Location: Bangalore

Work Mode: Hybrid

Job Description:

- Lead cross-functional projects using advanced data modeling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities.

- Build, develop, and maintain analytical models that support key business decisions.

- Work on advanced analytics and AI/ML projects to find business opportunities and improve processes.

- Oversee the scaling of analytics projects on cloud platforms to ensure seamless functionality and integration with business operations.

- Engage with stakeholders to understand their business needs, formulate and complete end-to-end analysis that includes data gathering, analysis, ongoing scaled deliverables, and presentations.

- Implement agile methodologies in all aspects of project life cycle, ensuring timely delivery of high-quality products.

- Drive the collection of new data and the refinement of existing data sources; assess the effectiveness and accuracy of new data sources and data gathering techniques.

- Develop custom data models and algorithms to apply to data sets, with a keen focus on financial and manufacturing domains.

- Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.

- Coordinate with different functional teams to implement models and monitor outcomes.

- Develop processes and tools to monitor and analyze model performance and data accuracy.

Qualification:

- Master's degree in Computer Science, Statistics, Applied Mathematics, or related field.

- 6+ years of experience in a data science role, with a focus on analytics and data modeling in cloud environments.

- Strong problem-solving skills with an emphasis on product development.

- Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.

- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.

- Excellent written and verbal communication skills for coordinating across teams.

- A drive to learn and master new technologies and techniques.

- Experience with cloud services (AWS, Azure, GCP) and understanding of scaling analytics projects in cloud environments.