You are a driven and motivated problem solver ready to pursue meaningful work. You strive to make an impact every day & not only at work, but in your personal life and community too. If that sounds like you, then you've landed in the right place.

The Hartford seeks energetic and passionate Machine Learning Engineer to design and build Machine Learning Operations (MLOps) framework for Personal Lines Data Science and Analytics teams. Our Data Science team has developed industry-leading capabilities, driving streamlined processes and smarter decision making. We support a variety of functions including Personal Lines Product, Underwriting and Sales. As a Senior Data Engineer within the Personal Lines Data Analytics Enablement organization, you will play a significant role ensuring delivery of reliable, reproducible and scalable MLOps framework and standardization on the cloud.

We are looking for talent who embraces our core values:

• We build solutions, not models. We are thoughtful in supporting the end-to-end business problem, with an eye to systems design.
• We are trusted and transparent. We collaborate tightly with our partners and are mindful of their capacity to absorb change.
• We provide assets that are safe to buy. Our products are delivered with a full monitoring solution to ensure our products continue to deliver as expected.
• We will earn the right to influence. With humble confidence, we listen carefully to learn from our customers and become partners in problem solving.
• We are practical and evolutional. We first deliver a minimally viable product and over time expand its sophistication based on feedback.

Responsibilities

• Design and Build MLOps ecosystem to support a rapidly expanding set of use cases, capabilities, and environments.
• Participate in Agile ceremonies to execute the MLOps roadmap to deliver ML models to production.
• Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.
• Collaborate with Data Engineering, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams to align the MLOps vision and strategy.
• Collaborate with partner teams to create architectural patterns and playbook for MLOps.
• Bring in new ideas and industry best practices to build state of the art analytical ecosystem to mature MLOps practice at enterprise level.

Minimum Requirements

• Strong presentation and communication skills to effectively collaborate with partner teams and influence the adoption of MLOps framework
• Experience in end-to-end model development lifecycle, from ideation through post production.
• Good understanding of DevOps, Machine Learning Model LifeCyle and Agile methodology.
• Delivery of critical milestones for model deployment in the cloud will be the primary success criteria for this position. Understanding the Data Science Model Development Process and the IT Software Development Lifecycle (SDLC) is essential for this role.
• 2+ years direct experience working with machine learning lifecycle, environments, and platforms
• Experience with Cloud technologies
• Exposure with CI/CD tools and continuous integration – Jenkins, Nexus, Git
• Basic understanding of ML frameworks (i.e. Scikit Learn, H20)
• Must be authorized to work in the U.S. now and in the future.
• Bachelor or Master’s degree in related field or 5+ years of equivalent experience in a research function.

Preferred Skills:

• Experience leading and managing software development and delivery teams.
• Experience with AWS MLOps Tools including CodeBuild, CodePipeline, CloudFormation, and Airflow
• Experience working with Docker and EC2 environment
• Experience with Snowflake cloud data platform
• Experience with Agile framework
• Conceptually strong with Cloud, Distributed processing and Container frameworks such as Dockers, EC2, Kubernetes, etc.
• Familiarity with Sage Maker, Python Flask or Spring Boot.
• Demonstrable interest in data science or predictive analytics
• Experience with Agile framework in a cross-collaboration environment.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

Benefits

Our company’s success is due to our employees’ dedication and passion for their work. They are our greatest asset. That’s why we are committed to offering employees and their families a comprehensive benefits package and award-winning well-being programs. By helping our employees achieve their full potential, we unlock our own. Visit https://www.thehartford.com/careers/benefits for details.

Equal Opportunity Employer/Females/Minorities/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age