Team - Data Insights
Department - Digital Business & Transformation
Team Size - 20+
Role Summary - Data Science Head will be responsible to establish the future technical product vision and lead all aspects of the technology product development.
- He/she should crave to go beyond traditional boundaries and be an - Out of the Box- thinker. He/ she should believe the customer should be at the centre of the solution and not the product.
- Revolutionary and disruptive in approach, the candidate should be passionate to make cutting-edge changes to the way financial services is delivered in India.
Key Responsibilities -
- Strategize and think about new ways to leverage traditional and big data
- Define data structures required and identify their sources
- Enhance data collection procedures to include information that is relevant for building analytic systems
- Extend company's data with third party sources of information when needed
- Processing, cleansing, and verifying the integrity of data used for analysis
- Lead the business analysis for different Digital Banking products
- Monitor business performance, analyze variance drivers, and provide periodic updates to senior management. Provide insight on key performance trends and identify risks/opportunities towards meeting business targets.
- Provide thought leadership to long-term strategic planning process by delivering insightful analysis and perspective.
- Support product managers and campaign managers in understanding key business drivers and drive actionable insights to improve the business top-line and bottom line.
- Lead a team of analyst(s) fostering a high performance culture.
Key Relationships - Product Team, Technology Team
Role Competencies -
- Subject matter expert on machine learning techniques and algorithms
- Experience with common data science toolkits, such as Weka, NumPy etc. and statistical applications such as SAS, SPSS, R, Revolution R, or similar statistical applications
- Experience with data visualisation tools, such as D3.js, GGplot, etc.
- Proficiency in using query languages such as SQL, Hive, Pig, Hadoop
- Good applied statistics skills, such as distributions, statistical testing, regression, etc.
- Good scripting and programming skills
- Strong analytic & problem-solving capabilities
- Tremendous drive towards results. Ability to persist against obstacles & get things done.
- Strong communication skills - ability to work with multiple product teams/stakeholders, understand key business objectives, and communicate complex concepts effectively to different audiences
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