Location Address: Hybrid - mostly WFH approx. 1/month in office
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.
Create and apply model and algorithm testing strategies to measure the effectiveness of models, and make ongoing changes
Build and maintain batch data pipeline for the projects (Airflow)
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) 3+ years of proven working experience as a Data Scientist, Machine Learning Engineer, or similar role
2) 3+ years of working experience with SQL and relational databases technologies/concepts for both
3) 2+ years of experience programming in Python or equivalent languages (eg. R)
4) 2+ years of production experience with statistical analysis, machine learning and digital analytics (e.g., hypothesis driven analysis, acquisition, and fraud/anomaly detection)
Nice-To-Have Skills:
1) Domain knowledge/experience with on digital authentication and digital fraud analytics.
2) Experience with Power BI and/or Tableau
3) Hands-on experience with Big Data/Cloud ecosystem (GCP)
4) Experience with log management system (e.g., Splunk)
Soft Skills Required:
Able to work in a fast-paced, constantly evolving environment and manage multiple priorities.
Excellent written, verbal, and interpersonal skills for executive level communication and collaboration
Pragmatic and capable of solving complex issues.
Strong experience working with a variety of cross-functional teams.
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