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Deliver Markets Sales commercial impact with hands-on analytics and AI/ML (uplift, win-rate, pipeline velocity, wallet share, coverage productivity)
Build a prioritised use-case pipeline (targeting, next-best action, coverage effectiveness) and ship to production with KPI definition and tracking
Engineer end-to-end solutions, personally coding/prototyping critical components from data prep and features to modelling, productionisation, monitoring, and support
Operationalise analytics/ML with trusted data, model governance, and delivery controls (CI/CD, deployment, monitoring) on Databricks/Spark and Snowflake
Lead senior stakeholders (Sales, Product, Risk/Compliance, CDO/CTO, SMAD/Quants, engineering/data) to align priorities, secure decisions, and deliver outcomes
Requirements
Demonstrated ability to deliver analytics and AI/ML end-to-end, writing production-grade code from problem framing through build, deployment, and adoption
Demonstrated ability to engineer trusted data and features (quality, lineage, reusable metrics) using Python/SQL on Databricks/Spark and Snowflake
Demonstrated ability to apply engineering discipline to analytics/ML (Git, automated testing, code review, and CI/CD) to ship reliable changes
Demonstrated ability to prioritise use cases with clear KPIs and run experiments that evidence commercial impact
Demonstrated ability to influence senior stakeholders and deliver at scale within governance (model risk, compliance, and controls)
Nice to have
Markets Sales analytics use cases (targeting, next-best action, coverage effectiveness, pipeline) plus market data and pre/post-trade analytics
Kafka and dbt exposure a plus
Hands-on coding in Python, SQL, and PySpark for pipelines and production analytics/ML
Java/C++ or kdb+/q a bonus
MLOps in a controlled environment: MLflow, registry/versioning, CI/CD (GitLab/Jenkins), drift/performance monitoring, documentation
Data governance practices and tooling: data quality checks, lineage/metadata, access controls, and privacy-by-design (e.g., fine-grained controls such as Immuta or equivalent)
Advanced analytics/AI (incl. GenAI where appropriate) for decision support, recommendations, or productivity