Data Scientist
About the role
[Company Name] is seeking a Data Scientist to turn our data into predictions and insights that shape products and strategy. You will frame business problems, build and validate models, run experiments, and work with engineers to put your work into production. This role fits someone who pairs strong statistical judgment with practical, business-minded thinking.
Responsibilities
- Partner with business teams to frame problems that data and modeling can solve
- Build, validate, and iterate on statistical and machine learning models
- Design and analyze A/B tests and other experiments
- Prepare and engineer features from large, messy datasets
- Work with engineers to deploy models and monitor performance in production
- Evaluate models for accuracy, robustness, and fairness
- Communicate results, uncertainty, and recommendations to non-technical audiences
- Document methods and maintain reproducible code
- Stay current on methods and evaluate when new techniques add real value
Requirements
- Strong programming skills in Python or R for data analysis and modeling
- Solid foundation in statistics, probability, and experimental design
- Hands-on experience with machine learning libraries such as scikit-learn, XGBoost, or PyTorch
- Proficiency in SQL for extracting and shaping data
- Experience validating models and choosing appropriate evaluation metrics
- Ability to explain technical results clearly to business partners
- Advanced degree in a quantitative field or equivalent applied experience
Nice to have
- Experience deploying models with tools such as MLflow, SageMaker, or Vertex AI
- Familiarity with causal inference methods
- Experience with large language models or natural language processing
- Domain knowledge in [Company Name]'s industry
Pay
[Pay range] · [Benefits summary]