Senior Analytics Solution Associate

Analytics Solution Associate Senior

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 into clear 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 enhance batch data pipelines (and support streaming where applicable) to produce curated, trusted datasets under guidance.
• Help develop analytics-ready layers (data marts/semantic views) with consistent metric definitions and documentation (data dictionary, lineage notes, runbooks).
• Implement and run data 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.
• Support feature engineering, model training, and evaluation, and document assumptions/limitations; follow guidance on leakage checks and bias/fairness considerations.
• Follow established MLOps practices: version control, reproducible runs, basic automated tests, monitoring inputs/outputs, and supporting retraining/rollback procedures.
• Adhere to security and data governance expectations (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 in code 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 in data analytics, data engineering, or ML/AI delivery.
• Working proficiency in SQL and comfort with data modeling fundamentals (tables, joins, dimensional concepts).
• Hands-on experience building analyses and dashboards in Tableau, and working with data in Snowflake (e.g., querying, validating datasets, supporting curated views).
• Working proficiency in Python (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 with MLOps tooling (experiment tracking/model registry, automated pipelines, monitoring concepts).
• Exposure to NLP/GenAI use cases in a governed enterprise environment.
• Awareness of streaming/CDC/event-driven patterns for near-real-time analytics or detection use cases.