Location: San Francisco
Bay area. (Must Be Local OR Who can relocate can be considered / someone
can work Hybrid)/Can relocate ** This role is Hybrid
Need 13-14 + 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.