Job Specifications
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).
Hands-on experience with time-series modeling and anomaly / changepoint / significant-movement detection(e.g., STL decomposition, EWMA/CUSUM, Bayesian/prophet-style models, isolation forests, robust statistics).
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.
About the Company
RandomTrees is a global provider of Data and AI services. Led by distinguished Industry experts with a passion to innovate with data. We help reinvent your enterprise with cutting edge Generative AI backed by our niche expertise to handle any type of data. We bring a unique set of data & and AI accelerators that help jumpstart & accelerate AI journey in the enterprise. Our differentiators are backed by the leading enterprise cloud partners and clients span across life sciences, Automotive and other manufacturing Industrie...
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