Job Description
About The Role
The role focuses on building, validating, and scaling statistical models and machine learning algorithms to drive strategic decisions and product features. The team works on high-impact problems ranging from predictive customer behavior modeling to algorithmic optimization of internal operations.
The role requires bridging the gap between raw data and actionable intelligence, collaborating with engineers to productionize models and translating complex mathematical concepts into clear business strategies for cross-functional stakeholders.
Key Responsibilities
The role focuses on building, validating, and scaling statistical models and machine learning algorithms to drive strategic decisions and product features. The team works on high-impact problems ranging from predictive customer behavior modeling to algorithmic optimization of internal operations.
The role requires bridging the gap between raw data and actionable intelligence, collaborating with engineers to productionize models and translating complex mathematical concepts into clear business strategies for cross-functional stakeholders.
Key Responsibilities
- Develop, evaluate, and deploy predictive models using Python, R, and SQL to address critical business challenges and optimize performance metrics.
- Design and execute rigorous A/B tests, multivariate experiments, and causal inference studies to measure the impact of new product features.
- Build scalable, automated feature engineering and data preprocessing pipelines in collaboration with data platform and engineering teams.
- Conduct deep-dive exploratory data analysis (EDA) on high-dimensional datasets to discover patterns, anomalies, and potential optimization vectors.
- Establish model monitoring pipelines to track performance degradation, data drift, and prediction latency in production systems.
- Present statistical findings and strategic recommendations to executive leadership through clear visualizations and structured communication.
- 3–6 years of experience as a Data Scientist, with a proven track record of deploying statistical and ML models into production environments.
- Strong proficiency in Python (including pandas, numpy, scikit-learn) and advanced SQL for processing and analyzing large-scale datasets.
- Solid theoretical foundation in statistics, probability, hypothesis testing, experimental design, and regression/classification techniques.
- Experience with distributed computing frameworks like PySpark or Databricks, and cloud data warehouses such as Snowflake or BigQuery.
- Master’s or PhD in Statistics, Computer Science, Applied Mathematics, Economics, or a related quantitative field.
- Bonus: Experience with deep learning frameworks (PyTorch, TensorFlow) or LLM API integrations for unstructured text analysis.
How to Apply
About Evlo AI
Evlo AI
Chicago, IL
Technology
Skills & Technologies
PythonGoScalaMachine LearningLLMTensorFlowPyTorchUI
Inferred from job description
Frequently Asked Questions
Where is the Data Scientist role at Evlo AI based?
The Data Scientist position at Evlo AI is based in Chicago, IL.
What industry is the Data Scientist position at Evlo AI in?
This Data Scientist role at Evlo AI is in the Technology sector.
What skills does the Data Scientist role at Evlo AI require?
Based on the job description, relevant skills for this role include Python, Go, Scala, Machine Learning, LLM, TensorFlow, PyTorch, UI.
How do I apply for the Data Scientist role at Evlo AI?
You can apply for the Data Scientist position at Evlo AI using the apply link on this page. Build a professional, ATS-optimised resume with Clever CV first to strengthen your application.
