Senior Software Engineer/Data Scientist
The Hartford (company site, opens in a new tab)4–6 yrsOn-siteDirect career pageEst. 14–28 LPA
Posted on 18 Sept
Reach people at The Hartford
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at The Hartford you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Build, evaluate, and deploy statistical and machine learning models (GLMs, GBMs) to meet complex business and regulatory needs.
- Manage third-party data relationships including data intake, validation, and vendor engagement to ensure data quality.
- Collaborate with business partners to translate analytical findings into clear, actionable recommendations and support model monitoring and governance.
Minimum Requirements
- 4 to 6 years of relevant experience in statistical modeling and machine learning.
- Bachelor's or Master's degree in Computer Science, Mathematics, Data Science, or closely related field.
- Strong Python (pandas, NumPy, scikit-learn) and SQL skills; experience with Git and Unix-based development environments.
- Experience with model validation, stability assessment, documentation, version control (GitHub), and experiment tracking (e.g., MLflow).
Ideal Candidate Profile
- Proven expertise in GLMs and GBMs with ability to assess model performance, stability, and avoid overfitting in production-ready environments.
- Experience working with multiple data sources and external vendors to ensure data quality and resolve discrepancies.
- Comfortable communicating complex analytical results to both technical and non-technical stakeholders and translating insights into business recommendations.