Data Scientist
Job details
Mathematics, Statistics & Information Sciences (Science & Technology) Capgemini is a global leader in consulting, digital transformation, technology and engineering services. The Group is at the forefront of innovation to address the entire breadth of clients’ opportunities in the evolving world of cloud, digital and platforms. Building on its strong 50-year+ heritage and deep industry-specific expertise, Capgemini enables organizations to realize their business ambitions through an array of services from strategy to operations. Capgemini is driven by the conviction that the business value of technology comes from and through people. Today, it is a multicultural company of 340,000 team members in almost 50 countries. With Altran, the Group reported 2019 combined revenues of €17billion. Job Responsibilities:
- Assess applicability of advanced analytics methods and machine learning techniques for business topics.
- Build methodology and conduct advanced analytics for related business problems.
- Generate business insights from analytics.
- Execute advance analytics projects and provide ad hoc analyses to business units.
- Pilot advanced analytics methods, tools and platforms.
- Design, develop and execute the required analytical algorithms, techniques and statistical methods to address and solve business problems and requirements.
- Ensure timely delivery of analysis and proactively manage delays / issues if any.
- Ensure high quality and accuracy in each deliverable.
- Provide support for business continuity of deliverables / analyses.
- Demonstrate efficiency through contributing to and applying bank-wide best practices in analytics and data.
- Understand the algorithms / methodologies related implications of advanced analytics solutions; and assist in defining the solutions to support any future business requirements.
- Bachelor degree or above in Economics, Finance, Math, Statistics or equivalent.
- Min. 4 - 6 years of experience in analytics related roles (banking experience is a plus)
- Communication skills to drive conclusions with business.
- Ability to generate analytical insights to business problems
- Hands on experience in handling and managing large quantum of data via appropriate tools and techniques.
- Deep expertise in data mining, analytical techniques and solutions.
- Good understanding and hands on experience on Dataiku.
- Modeling experience (e.g. propensity, segmentation, demand forecasting).
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