Location:
San Francisco Bay area. (Must Be Local / someone can work Hybrid)/Can
relocate ** This role is Hybrid
Need
14 + years of Experience candidates
Key
Responsibilities
Design and productionize models for
opportunity scanning, anomaly detection, and significant change detection
across CRM, streaming, ecommerce, and social data.
Define and tune alerting logic (thresholds,
SLOs, precision/recall) to minimize noise while surfacing high-value
marketing actions.
Partner with marketing, product, and data
engineering to operationalize insights into campaigns, playbooks, and
automated workflows, with clear monitoring and experimentation.
Required
Qualifications
Strong proficiency in Python (pandas,
NumPy, scikit-learn; plus experience with PySpark or similar for
large-scale data) and SQL on modern warehouses (e.g.,
BigQuery, Snowflake, Redshift).
Experience building and deploying production
ML pipelines (batch and/or streaming), including feature
engineering, model training, CI/CD, and monitoring for performance and
data drift.
Solid background in statistics and
experimentation: hypothesis testing, power analysis, A/B testing
frameworks, uplift/propensity modeling, and basic causal inference
techniques.
Familiarity with cloud platforms (GCP/AWS/Azure),
orchestration tools (e.g., Airflow/Prefect), and dashboarding/visualization tools
to expose alerts and model outputs to business users.