Data Scientist

Department - Business Intelligence Unit

Report to: Head - BIU

A. Position Summary:

• S/he will be spending most of their time analyzing data. Past trends, current conditions, etc.
• S/he will be working on creating models for Digital platform to address UW, Personalized offers/ messaging.
• S/he is able to interpret large chunks of data, understand trends, analyze results, use of statistical techniques, visualization tools to give actionable insights.
• S/he should have worked on metrics tracking, modeling and MIS related to digital leads.

B. Key Responsibilities:

• Checking for trends and identifying anomalies
• Create Machine Learning model for Fraud, Underwriting, Early Claims, Propensity to Pay, Propensity to Surrender
• Create Machine Learning model to customize content and product offerings for online customer based on their customer segmentations
• Analyzing online user behavior, conversion data, customer journeys, funnel analysis and multi-channel attribution
• Formulate marketing hypothesis and test the same using statistical techniques
• Use models to predict and determine how prospective leads should be allocated
• Collecting and interpreting data
• Reporting the results, creating funnel and report insights back to the relevant stakeholders
• Working alongside teams within the business or the management team to establish business needs
• Defining new data collection and analysis processes

C. Job Specifications:

Qualifications:

• Candidate should have B.Tech in computer science, Masters/MBA is preferable
• Past experience working on Machine Learning, Data modelling and Visualization reports/Dashboards

Experience:

• Should have 4-6 years of experience in Insurance/ Banking/Lending/ Credit Bureau or Financial sector
• Extensive hands-on experience in working with Python, Pandas, Numpy, Seaborn, data modeling, feature engineering and developing ML models
• Extensive hands-on experience in working with Excel, SQL, PowerBI
• Should have good knowledge and working experience in creating reporting datasets, creating data refresh strategy and implementing role based data security on reporting tools
• Should have good knowledge and working experience in story-telling and presenting actionable insights to stake holders
• Contribute to knowledge base and mentor team members
• Good to have expertise on BI Tools
• Good to have knowledge on AWS, Sagemaker, Amazon S3, Cloudwatch
• Good to have knowledge in CI/CD pipelines, ML ops.

D. Key Technical Skills and Core Behavioral Competencies

• Well versed in all relevant technologies i.e. Machine Learnings, SQL, Python, Reporting, Dashboard, Feature Engineering, Marketing, AWS, ML ops
• Strong experience in Modeling , Reporting, Trend Analysis
• Demonstrated business orientation, correctly analyze business situation and foresee implications of major decisions with in-depth understanding of regulatory issues backed by strong business acumen
• Conceptual thinking - takes the right factors into account when developing solutions and demonstrate analytical thinking.
• Drive for results - Passion for learning and development, focuses on continuous improvement regarding work processes and able to work hard to achieve set goals.
• The candidate should possess the tact and ability to negotiate with and manage multiple stakeholders including board members, shareholders and regulatory authorities
• Strong interpersonal skills. Resourceful self-starter, proactive, results and execution-oriented team player Entrepreneurial spirit, pro-active attitude, be self-driven and detail oriented, possess excellent business judgment and excellent networking and relationship management skills
• Strong organizational skills with ability to manage multiple priorities. High energy levels, and works well under pressure to meet deadlines
• Proven ability to lead and manage projects and deliver business results, in a rapidly changing and cross-functional matrix environment
• Experience leading/managing and empowering others, and ability to work effectively in a culturally diverse international work group
• Process orientation with continuous improvement methodology
• Resourceful, pragmatic and realistic approach to analysis with limited data and time
• A sincere, well-intentioned professional with strong ethical values.