Senior Data Scientist - Banking Financial Services - Hybrid - Jakarta
Deskripsi Pekerjaan
ADECCO INDONESIA - SENIOR DATA SCIENTIST - WE ARE HIRING!! Role : Data Scientist Working Location: Jakarta - Hybrid (3 WFO & 2 WFH)
Working Days : Monday - Friday 09.00 - 18.00 WIB Employee Status: 12 months contract under Adecco Indonesia (Renewable/Extendable) Our Client is a global leader in payments and technology, with more than 259 billion payment transactions processed securely between consumers, merchants, financial institutions, and government entities across more than 200 countries and territories each year. Our Client's mission is to connect the world through an innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while contributing to a more inclusive and connected world.
Our Client's Consulting and Analytics team is the consulting arm of the organization, focused on delivering tangible and impactful results for clients. Drawing on expertise in consulting, data analytics, digital marketing, and economics, the team addresses strategic business challenges and develops data-driven solutions to support clients in achieving their objectives. The Intelligence & Data Solutions (IDS) team consists of data scientists, analysts, and engineers who develop and deliver advanced analytics solutions. The team leverages one of the world's largest payment datasets to help clients enhance business performance, generate actionable insights, and increase profitability.
The individual will be responsible for the delivery and implementation of analytics-driven strategies and high-impact solutions for Our Client's customers. The role requires deep expertise in banking and payments , combined with a strong background in data science and analytics , to solve complex business problems and unlock measurable business value. We are looking for a motivated and analytical professional with a proven track record of leveraging data science and analytics to unlock business value . The successful candidate should have diverse industry experience, a strong interest in the payments industry and the application of data science , and a results-driven and client-centric approach.
Bachelor's degree or higher in a quantitative discipline such as Statistics, Mathematics, Physics, Computer Science, Economics, Engineering , or an equivalent combination of education and experience. A Master's or Ph.D. degree is preferred. 6+ years of professional experience , preferably within banking, payments, fintech, or related industries . Hands-on experience with data analytics and programming tools , including Python, R , and advanced SQL or other query languages.
Tanggung Jawab
- Engage with clients to define and validate KPIs, event taxonomies, segmentation logic, and data quality expectations , while clearly documenting definitions and assumptions
- Coordinate data requests, data ingestion specifications, secure data transfer requirements, and validation processes; troubleshoot data gaps and inconsistencies with client data owners
- Analyze and interpret data using statistical programming tools such as Python and R
- Extract, transform, and aggregate large datasets using SQL, Hive, Spark , and other data processing tools
- Deploy, maintain, and support predictive modeling solutions, including monitoring and calibrating production models
- Apply innovative data science and advanced analytics techniques to solve complex business problems
- Collaborate with data science colleagues and cross-functional teams to develop and deliver actionable insights to clients
- Automate analytical processes and develop repeatable analyses or self-service analytics tools
- Ensure timely delivery of analytics projects in line with business requirements and client expectations
- Promote data innovation and analytics knowledge sharing within the organization
- Optimize code and analytical processes supporting critical business requirements
- Design and develop data visualization dashboards using tools such as Tableau and Power BI
- Communicate complex analytical concepts and insights clearly and effectively to both technical and non-technical stakeholders
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