Typical Day in Role:
• Collaborate with business lines and other stakeholders and identify opportunities to drive business value by leveraging data science and data engineering solutions?
• Efficiently handle large volumes of structured and unstructured data through ingestion, modeling, transformation, and storage across diverse data stores. Leverage distributed computing tools (e.g., Spark, Cloud) for analysis, data mining, and modeling
• Collaborate with operation, and other analytics teams to deploy models and algorithms in production across different channels and platforms?
• Work with the team to design the project architecture and road map.
• Prepare detailed documentation to outline data sources, models, and algorithms used and developed.?
• Present results to business line stakeholders and help implement real world data-driven changes.
Candidate Requirements/Must Have Skills:
1) 10+ years of combined working experience with SQL, Spark and relational databases technologies/concepts for both
2) 10+ years of production experience with statistical analysis, machine learning and digital analytics (e.g., hypothesis driven analysis, acquisition, and fraud/anomaly detection)
3) 3-5+ years’ experience with Power BI and/or Tableau (Power BI preferable)
Nice-To-Have Skills:
1) Domain knowledge/experience with on digital authentication and digital fraud analytics.
2) Hands-on experience with Big Data/Cloud ecosystem (GCP)
3) Experience with existing Know-Your-Customer (KYC) practices across financial institutions and the supporting technologies
Soft Skills Required:
• Excellent written, verbal, and interpersonal skills for executive level communication and collaboration
• Able to work in a fast-paced, constantly evolving environment and manage multiple priorities.
• Pragmatic and capable of solving complex issues.
• Strong experience working with a variety of cross-functional teams.
Education:
Bachelor’s Degree or equivalent in in Computer Science, Engineering, or relevant field.