Data Scientist Senior Associate — Business Observability & AI Platform
Salary not listed • Jersey City, NJ, United States • Full-time
Posted 1mo ago
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Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Join a fast-moving technology team building a business observability platform for the Payments business. This platform serves as an analytics foundation enabling AI-assisted decision-making for senior leaders and real-time monitoring and alerting for operations teams. The role will contribute to delivering intraday transaction insights, anomaly detection, forecasting, and conversational analytics, all supported by a governed metrics foundation. As a Data Scientist Senior Associate, you will be responsible for the analytical integrity of the team's deliverables, validating data behind key metrics, defining model correctness, and ensuring the trustworthiness of anomaly detection and forecasting outputs in production. You will collaborate closely with product, engineering, and design teams to influence the product roadmap and effectively communicate value to stakeholders.
Responsibilities
- Perform exploratory and diagnostic data analysis on large-scale transactional datasets to validate business logic, metric definitions, and data quality.
- Define and document acceptance criteria for analytical features, metrics, and model behavior, and verify releases against them.
- Design and execute validation and back-testing for anomaly detection and forecasting models, assessing metrics like accuracy, precision/recall, and false-positive rates.
- Build and operate model and data drift monitoring systems, recommending retraining or recalibration when performance degrades.
- Investigate and triage analytical defects, reconciliation breaks, and unexpected model outputs with upstream data and platform teams.
- Create clear data visualizations and analytical narratives for executive and operational audiences.
- Contribute to product demos and stakeholder materials.
- Partner with the Technical Product Owner on requirements, user story refinement, and prioritization based on data evidence.
Requirements
- Bachelor's degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Economics, Engineering, or similar).
- 2+ years of applied data analysis or data science experience, or an advanced degree with relevant internship/project work.
- Strong SQL skills, including analytical functions and performance-aware querying.
- Proficiency in Python and the standard analytics stack (pandas, NumPy, scikit-learn, statsmodels or equivalent).
- Working knowledge of time series analysis, forecasting methods, and anomaly detection techniques.
- Practical experience with data quality testing, validation frameworks, and reconciliation.
- Ability to build clear, decision-ready visualizations and communicate findings to non-technical stakeholders.
- Comfort working in an agile, high-ownership environment with shifting priorities.