Senior Data Scientist
Core
Building production generative AI, autonomous agents, and predictive models for churn, LTV, and pricing to power marketing technology and data intelligence for regulated industries.
Role type
Senior IC machine-learning engineer (generative AI & agentic systems)
Builds
Production ML models, agent-based systems, and intelligent features for customer-facing tools
Domain
Marketing technology & data intelligence for healthcare, automotive, insurance, and finance
Deliverable
production ML models
Required skills
Python (Pandas, NumPy, Scikit-learn), PyTorch, TensorFlow, Hugging Face, LangChain, SQL, cloud data warehousing (Snowflake, BigQuery, Redshift), AWS (Lambda, SageMaker, EC2, Batch, S3), ETL/pipeline orchestration (Airflow), LLMs, generative AI applications (NLP, content synthesis, summarization, retrieval)
Preferred skills
probabilistic modeling (PyMC3, Stan), graph databases (Neo4j), recommendation engines, survival models, multi-touch attribution, LLM deployment/evaluation, BI platforms (Looker, Tableau)
Technologies
MLflow, SageMaker, Vertex AI, Airflow, Snowflake, BigQuery, Redshift, AWS Lambda, AWS SageMaker, AWS EC2, AWS Batch, AWS S3, PyTorch, TensorFlow, Hugging Face, LangChain, PyMC3, Stan, Neo4j
Responsibilities
Architect, prototype, and productionize ML models including generative AI and recommendation systems; Build agent-based systems that reason, retrieve, validate, and act autonomously; Coach junior and mid-level data scientists and engineers; Work with Product, Engineering, Design, and GTM teams to integrate intelligent systems; Develop models for customer LTV, churn, content efficacy, user engagement, and pricing optimizations; Contribute to architecture decisions on model lifecycle management, pipelines, monitoring, and experiment tracking
Seniority
Senior, hands-on IC