Deputy Unit Manager - Payments - Data Science

Job Purpose
Individual responsible for leveraging Business Intelligence & Analytics skill to get insights that can be used by Businesses to their AOP targets. Duties and Responsibilities
Planning
Engaged closely with internal teams and stakeholders to understand their data requirements, developed a strategic roadmap outlining key tasks and initiatives, and effectively communicated these priorities to the team for seamless execution.
Involved in cross-functional collaboration with various stakeholders, including the Risk Team and IT Team.

Business intelligence
Collaborate with internal teams to ensure dashboards and BI tools are utilized effectively and align with business needs.
Monitor regularity and accuracy of data flow to the business teams.
Leverage Big Data tools and innovative modeling techniques to develop robust solutions that address business challenges and enable predictive insights.
Assist in the development and refinement of predictive modeling infrastructure to enhance processes, performance, and testing capabilities.
Deliver data insights and BI that are accurate and informative to enable the business to make data-driven content and learner experience decisions.
Work with large, complex data sets whilst solving challenging business problems independently and across teams
Define, build, and monitor hourly, daily, and monthly KPIs, creating improvement strategies based on insights.
Manage ad-hoc data insights, Trend analysis requests from business team.
Conduct thorough quality assurance of the data feeds as well as the analytical capabilities.
Develop compelling summaries that visualize the data through narrative dashboards to clearly tell a succinct story in easy-to-understand ways.
Demonstrate analytic curiosity and a desire to understand challenges to contribute to matrix team reviews and strategic discussions for insight discovery Key Decisions / Dimensions
Analyze the user behavior and engagement.
Delivery Timeline related.
Adapting & Implementing industry best practices
Data Analysis and Value creation
Create insights from predictive statistical modeling, mathematical knowledge, tools, and techniques to solve complex problems and deliver value
Collaborate with Business teams to address business issues and influence change using strategy, industry, and analytical skills Major Challenges
Co-ordination between multiple teams (Risk, IT, 3in1) and external vendors to enable task delivery.
Providing rightful solutions to Business problems with data driven insights
Co-ordination with IT teams for any new development.
Daily sync with EDW team for data quality checks.
Enabling controls on data sanity and build data engineering pipeline.
Efficiently construct, develop, and implement the models in a variety of modeling tools, achieving highly accurate models Required Qualifications and Experience
a) Qualifications
Bachelor s degree in computer science, Math, Physics, Engineering, or related quantitative field or Post-graduate from a reputed institute with a minimum 6 years of experience as a Data Scientist in Fintech/Payment/Relevant Industry.
Work Experience
Minimum of 6 - 8 Years of experience Leading Data Scientists & Data Analysis
Experience with common data science toolkits, such as Python (Pandas, NumPy, Sci-kit, SciPy etc.)
Great communication skills (ability to convert data language to business language)
Experience with data visualization tools, such as Power BI, PlotLy, Matplotlib etc.
Proficiency in using query languages such as SQL, Spark SQL is mandatory.
Experience with NoSQL databases, such as MongoDB, Cassandra will be a plus
Good, applied statistics skills, such as distributions, statistical testing, regression, etc.
Good scripting and programming skills (Python/R)