The Sr Manager of Data Science is a key role within the Central Europe, Middle East and Africa (CEMEA) Data Science risk team, focusing on innovative and analytical strategies to enhance data-driven approaches in the region. This position will engage in the development of predictive and prescriptive models, and the creation of context-based prototypes and impactful storyboards that advocate for data-driven strategies and solutions tailored for the company clients. The role primarily encompasses areas related to credit, fraud, operational risks, deep risk analytics, risk scoring, and forecasting solutions.
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Principal Responsibilities
- Focuses heavily on creating and implementing top-tier risk analytic solutions, including developing scoring and non-scoring models, as well as delivering impactful insights through enhanced visualization and storyboarding.
- Collaborates with a diverse team including Business Managers, Consultants, and Data Scientists from both the company and client organizations to strategize, co-create, deploy, and maximize the benefits of data-driven solutions.
- Partners with regional and global Data Science teams to produce high-quality analytic products that facilitate the company’s growth in the region.
- Stays ahead of technological advancements in Data Science, integrating cutting-edge tools and methodologies for generating business insights.
- Works closely with internal Technology partners and the Data Engineering function to optimize the use of the company’s technological platforms and data resources, addressing clients’ technical data requirements effectively.
- Manages personal workload and directs reports, offering prioritization guidance to enhance project flow and process efficiency.
Work Conditions
This is a hybrid position. The expectation for days in the office will be determined by your hiring manager.
Qualifications
- A minimum of 8+ years of experience applying Machine Learning solutions to business problems, including model development and production.
- A post-graduate degree (Masters or PhD) in a quantitative discipline such as Statistics, Mathematics, Data Science, Operational Research, Computer Science, Informatics, Economics, or Engineering.
- Strong knowledge and experience in quantitative techniques (modeling, statistics, root-cause analysis) specific to Risk Management, particularly in the Card and Payments sector.
- Proficiency in multiple programming languages including Python, R, Scala, Java, Matlab, C++, and SQL.
- Demonstrated ability to achieve results within agreed scope, timelines, and budget.
- Willingness to travel within CEMEA on short notice, with an expected travel rate of 40-60%.
