AVP - Data Analyst - Digital - Bank

AVP - Data Analyst - Digital - Global Bank - Women only

Job Purpose:

- Identifying the Opportunities for Business growth

- Support business in meeting the Budgets through Analytical Insights

- Communicate results and ideas to key decision makers

Key Accountabilities:-

- Regular Portfolio Health Check-ups through Business Insights

- Identifying areas of growth and areas of sluggishness within portfolio

- Drive insight led actionable to help achieve portfolio targets

- Support Stakeholders in Business Reviews

- Support key business initiatives for data driven decisioning

Job Duties & responsibilities:

- Structure, define and execute data analysis to uncover insights and inform decision making for digital bank.

- Collaborate with regional & local counterparts to define and align performance metrics.

- Support ad-hoc data requests for management meetings.

- Formulate requirements and work with data engineering and technology team to develop and validate .

- Automated data pipelines for business performance dashboards.

- Engage with business and product teams on the problem formulation and create solution framework.

- Design A/B test experiments to test the model effectiveness and Analyze to identify the target segments.

- Drive the testing and deployment of the machine learning products into production.

- Understand the Product Journeys and help business to improve the customer experience.

Required Experience:

- Strong academic background

- Should be self-motivated and adaptable.

- Should possess a creative bent of mind and should be a strategic thinker.

- Should be focused and well organized

Technical Experience:

- Relevant years of experience in Data Science/Analytics (consumer banking, ecommerce, retail, telecoms, technology) with demonstrated track of generating value through data driven solutions.

- Should have full understanding of applications of DS/ML/AI solutions to various business problems.

- Proficiency in using databases like Teradata, NoSQL and Hadoop using SQL, Hive, Spark, etc.,

- Programming experience in Python, R, Spark, SAS, Tensor-Flow or other machine learning oriented programming languages/platforms.

- Good understanding of technology tools especially those related to analytics, data & modelling.

- Ability to communicate complex analysis/models across a diverse team.

- Good written and oral communication skills.