- Company Name
- HL Solutions LLC
- Job Title
- Senior Data Scientist With Snowflake
- Job Description
-
**Job Title**
Senior Data Scientist (Snowflake)
**Role Summary**
Lead the end‑to‑end development, deployment, and operationalization of advanced machine‑learning and statistical models within the Snowflake ecosystem. Drive strategic insights, ensure high‑performance in‑warehouse analytics, and mentor junior talent while maintaining best practices in model rigor and data engineering.
**Expectations**
- Deliver production‑ready ML solutions that meet business objectives (e.g., churn prediction, sales forecasting, risk modeling).
- Own model lifecycle—design, train, validate, deploy, monitor, and retrain models using Snowpark, Snowflake UDFs, and external functions.
- Collaborate with data engineering and product teams to integrate ML pipelines into CI/CD workflows.
- Communicate findings and model impact to technical and non‑technical stakeholders through data storytelling and visualization tools.
**Key Responsibilities**
- Design and implement predictive, prescriptive, clustering, and forecasting models; validate with cross‑validation and performance metrics.
- Perform large‑scale feature engineering in Snowflake using advanced SQL and Snowpark (Python/Scala).
- Conduct A/B testing and causal inference studies to quantify business impact.
- Build and maintain scalable ML pipelines, automate retraining with Airflow, dbt, or similar orchestration tools.
- Monitor model performance (drift, bias, accuracy) and operational health within Snowflake, establishing alerting and remediation processes.
- Create dashboards and visualizations (Tableau, Power BI, or Snowflake Streamlit) to translate analytics into actionable insights.
- Champion statistical rigor, coding standards, and efficient data processing within the Snowflake data cloud.
- Mentor junior data scientists and analysts on modeling techniques and Snowflake features.
- Evaluate and incorporate new Snowflake capabilities (Generative AI, LLMs, Unistore, Data Sharing) to generate business value.
**Required Skills**
- Expertise in Python (scikit‑learn, NumPy, Pandas) and scalable data processing.
- Mastery of Advanced SQL for complex data manipulation and feature engineering.
- Proven experience with ML algorithms, statistical modeling, and causal inference.
- Deep understanding of MLOps principles—model lifecycle, CI/CD, monitoring, and drift detection.
- Hands‑on proficiency with Snowflake (Snowpark, UDF/UDTF, external functions, Streamlit).
- Familiarity with cloud ML services (AWS SageMaker, Azure ML, GCP Vertex AI) and integration with Snowflake.
- Experience with workflow orchestration tools (Airflow, dbt).
- Strong analytical, problem‑solving, and communication skills.
**Required Education & Certifications**
- MS or Ph.D. in a quantitative discipline (Statistics, Computer Science, Engineering, Economics, Mathematics).
- 7+ years of progressive data science experience, 3+ years deploying ML in a cloud data warehouse environment, preferably Snowflake.
- Snowflake SnowPro Advanced: Data Scientist Certification (preferred).