Applied Data Scientist / Machine Learning Engineer (Decision Intelligence)
Core
Build, ship, and scale ML-powered SaaS products (forecasting, recommendation, ranking, optimization) that improve customer decision-making and business operations.
Role type
Senior Applied Data Scientist / Machine Learning Engineer (Product)
Builds
Customer-facing SaaS products with embedded ML capabilities
Domain
SaaS, Decision Intelligence, Operational Intelligence
Deliverable
production ML models
Required skills
Python, SQL, Scikit-Learn, XGBoost, PyTorch, TensorFlow, supervised learning, forecasting, ranking, recommendation systems, optimization, statistical modeling, MLOps, Airflow, dbt, Dagster, Snowflake, BigQuery, Redshift, Databricks, AWS, GCP, Azure
Preferred skills
Decision intelligence, customer behavior modeling, workforce/route optimization, LLMs, GenAI, agentic workflows, senior/lead scientist experience
Technologies
Scikit-Learn, XGBoost, PyTorch, TensorFlow, Airflow, dbt, Dagster, Snowflake, BigQuery, Redshift, Databricks, AWS, GCP, Azure
Responsibilities
Drive end-to-end ML ownership from problem definition to production deployment and monitoring; Design reliable data and feature pipelines; Partner with Product Managers and Software Engineers to embed ML into product workflows; Define offline and online evaluation strategies and design A/B tests; Collaborate with Data teams to ensure high-quality features and build feedback loops; Manage and optimize cloud data infrastructure; Guide and mentor other data scientists and cross-functional partners
Seniority
Senior, hands-on IC with mentorship responsibilities