This is a 10 - month renewable contract with our client in the Fintech industry. Core Purpose To automate data pipelines and structure datasets to build advanced product capabilities. This role focuses on leveraging statistical techniques, machine learning, and decision models to provide actionable insights and reporting across multiple operational territories. Key Responsibilities Data Engineering: Automate data ingestion, transformation, and visualization processes; collaborate with engineering teams on new data architectures. Advanced Analytics: Build predictive models for volumes and transaction patterns; perform optimization, text analytics, and social-science modeling. Product Support: Develop decision models and data-based rules to support product roadmaps and enhance targeting capabilities. Risk & Compliance: Implement ML-driven fraud detection and monitor transaction data for regulatory compliance. Business Intelligence: Create automated dashboards and scorecards (Power BI/Tableau) to track KPIs and operational performance. Minimum Requirements Education: 4-year degree in Data Science, Statistics, Mathematics, or a related field. Experience: Minimum 5 years in Financial Services, Analytics, or Consulting. 2–3 years in data structuration and big data environments. 1–2 years at a specialist level in Data Science (Banking/Fintech/Telco preferred). Python: (Numpy, Pandas, Scikit-learn, Tensorflow) or R/Scala. Big Data: Hadoop, Apache Spark, Hive, or MapReduce. Databases: SQL (Postgres, Oracle, MSSQL) and NoSQL (Mongo). Cloud: Microsoft Azure.