Data Scientist at DS Technologies Inc in CA-San Francisco-94101

Job description

• DS Technologies Inc is looking for Data Scientist role for one of our premier clients.

Responsibilities

• Primary focus : Model reproduction, feature engineering logic, performance validation, and ensuring alignment with Client's established modeling frameworks.
• • Rebuild and port existing Clilent's Python based models into customer’s Databricks platform.
• • Develop, train, and validate predictive models using Python, PySpark, and ML frameworks such as scikitlearn, XGBoost, and Spark MLlib.
• • Develop, validate and reproduce feature engineering logic and ensure parity with Client's models.
• • Train, retain, validate, and benchmark model performance using customer provided datasets while maintaining performance parity with baseline models.
• • Work with data engineers to define feature requirements and ensure datasets support model needs.
• • Perform model diagnostics, bias checks, stability checks, and accuracy assessments.
• • Prepare model documentation, validation summaries, and stakeholder ready insights.
• • Support scoring pipeline design and ensure reproducibility across Dev/QA/Prod.
• • Collaborate with compliance and platform teams to ensure adherence to governance.
• • Perform model diagnostics, hyperparameter tuning, and stability analysis.
• • Evaluate model performance across population segments and time periods.
• • Work with platform and engineering teams to support scoring pipeline deployment across Dev/QA/Prod.

Requirements

• • 4–6 years of experience in applied machine learning or data science.
• • Strong hands-on experience with Python, scikit-learn, XGBoost, LightGBM, CatBoost, or similar libraries.
• • Experience developing ML models in Databricks with Python or PySpark.
• • Strong knowledge of feature engineering, model training workflows, and evaluation techniques.
• • Experience working with large structured datasets (financial or transactional data preferred).
• • Ability to write clear documentation and communicate technical results to non-technical stakeholders.
• • 4+ years of hands-on experience developing, deploying, and maintaining machine-learning models.
• • Advanced proficiency in Python (NumPy, pandas, scikit-learn, PyTorch or TensorFlow).
• • Strong statistical and mathematical foundation, including regression, classification, probability, optimization, etc.
• • Experience building end-to-end ML pipelines: data ingestion, cleaning, feature engineering, modeling, evaluation, deployment.
• • Experience working within client environments, including adapting to unfamiliar infrastructure, constraints, and security requirements.
• • Experience with cloud platforms (AWS, Azure, or GCP) and on-prem environments.
• • Advanced SQL ability and experience with big-data tools (Spark, Databricks, Hadoop).

Skills

Required

• Python
• PySpark
• scikit-learn
• XGBoost
• LightGBM
• CatBoost
• Databricks
• Spark
• Hadoop
• SQL
• AWS
• Azure

Benefits

• Compensation: $150,000.00 per year