Data Scientist
Evlo AIAbout the role
About The Role
The role owns the end-to-end data science lifecycle, turning complex datasets into predictive insights and robust machine learning models that drive core business decisions.
You will partner closely with data engineers, product managers, and software teams to build scalable analytics infrastructure and advanced statistical algorithms.
Key Responsibilities
Develop and deploy advanced machine learning models and statistical algorithms using Python and SQL for core business applications
Design and execute rigorous A/B tests to measure feature impact and validate algorithmic improvements
Build automated data cleaning, transformation, and feature engineering pipelines operating on large-scale datasets
Collaborate with data engineering teams to optimize data storage, retrieval, and schema design for modeling workflows
Present actionable insights, technical findings, and model performance metrics to cross-functional stakeholders
Monitor deployed production models for performance drift and implement retraining strategies
What We Are Looking For
3-6 years of experience in data science, quantitative analysis, or applied machine learning within production environments
Advanced proficiency in Python, SQL, and core data science libraries such as Pandas, NumPy, scikit-learn, and PyTorch
Demonstrated experience designing and analyzing large-scale A/B experiments and statistical hypothesis testing
Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization tools like Docker
BS or MS in Statistics, Applied Mathematics, Computer Science, or a related quantitative field
Bonus: Experience with LLM integrations, PySpark, or real-time streaming architectures
Responsibilities
- Develop and deploy advanced machine learning models and statistical algorithms using Python and SQL for core business applications
- Design and execute rigorous A/B tests to measure feature impact and validate algorithmic improvements
- Build automated data cleaning, transformation, and feature engineering pipelines operating on large-scale datasets
- Collaborate with data engineering teams to optimize data storage, retrieval, and schema design for modeling workflows
- Present actionable insights, technical findings, and model performance metrics to cross-functional stakeholders
- Monitor deployed production models for performance drift and implement retraining strategies
Qualifications
- 3-6 years of experience in data science, quantitative analysis, or applied machine learning within production environments
- Advanced proficiency in Python, SQL, and core data science libraries such as Pandas, NumPy, scikit-learn, and PyTorch
- Demonstrated experience designing and analyzing large-scale A/B experiments and statistical hypothesis testing
- Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization tools like Docker
- BS or MS in Statistics, Applied Mathematics, Computer Science, or a related quantitative field
- Bonus: Experience with LLM integrations, PySpark, or real-time streaming architectures
Skills mentioned
About Evlo AI
Powering the Nex Generation Frontier Models and Intelligence by connecting best talent with best companies