Deliver analytics data products & AI/ML solutions end-to-end: define KPIs, build pipelines, ensure quality, support MLOps & controls.
As an Analytics Solution Associate in Consumer & Community Banking, you will support the delivery of analytics data products and applied AI/ML solutions. You will contribute across the delivery lifecycle-problem definition, requirements, data engineering, basic model development, production support, and documentation-while partnering with Product, Technology, Data Governance, and Risk/Controls.
Job Responsibilities
- Support stakeholders in translating business needs intoclear problem statements, KPIs, and success metrics(e.g., servicing insights, customer engagement, marketing measurement, forecasting, anomaly detection).
- Assist in maintaining delivery hygiene:action items, RAID logs, dependency tracking, and status updates.
- Build and enhancebatch data pipelines(and support streaming where applicable) to produce curated, trusted datasets under guidance.
- Help developanalytics-ready layers(data marts/semantic views) with consistent metric definitions and documentation (data dictionary, lineage notes, runbooks).
- Implement and rundata quality checks(tests, reconciliations, completeness/timeliness checks) and support monitoring/alerting and SLA tracking.
- Contribute to ML use cases (e.g., propensity/segmentation, next-best-action components, forecasting, anomaly detection, basic NLP for servicing insights) under senior oversight.
- Supportfeature engineering, model training, and evaluation, and document assumptions/limitations follow guidance on leakage checks and bias/fairness considerations.
- Follow establishedMLOpspractices: version control, reproducible runs, basic automated tests, monitoring inputs/outputs, and supporting retraining/rollback procedures.
- Adhere tosecurity and data governanceexpectations (least-privilege access, sensitive data handling, retention, auditability).
- Produce required delivery and control artifacts (documentation, traceability, operational procedures) and support control reviews/audits.
- Apply SDLC practices: participate incode reviews, follow CI/CD patterns, support environment promotion, and assist with incident triage/root-cause analysis.
Required Qualifications, Capabilities, and Skills
- 4+ years (or equivalent) experience indata analytics, data engineering, or ML/AI delivery.
- Working proficiency inSQLand comfort with data modeling fundamentals (tables, joins, dimensional concepts).
- Hands-on experience building analyses and dashboards inTableau, and working with data inSnowflake(e.g., querying, validating datasets, supporting curated views).
- Working proficiency inPython(or similar) for data processing and basic ML workflows.
- Exposure to modern data platforms (warehouse/lakehouse concepts) and orchestration tools.
- Basic understanding of the applied ML lifecycle (framing→ build→ deploy→ monitor) and common evaluation metrics.
- Comfort operating in a controlled environment (change management, access controls, documentation expectations).
- Strong communication skills and ability to work effectively across teams with guidance.
Preferred Qualifications, Capabilities, and Skills
- Exposure to consumer banking/retail analytics domains (servicing, digital, customer insights).
- Familiarity withMLOpstooling (experiment tracking/model registry, automated pipelines, monitoring concepts).
- Exposure toNLP/GenAIuse cases in a governed enterprise environment.
- Awareness of streaming/CDC/event-driven patterns for near-real-time analytics or detection use cases.
