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Machine Learning Engineer - Data Science
  • Python
  • Spark
  • SQL
  • Linux
  • Machine Learning
  • Modeling
  • Hadoop
  • Scala
The Hartford
Hartford, CT
117 days ago
Sr Data Engineer - GE07BE

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.

Senior Machine Learning Engineer

The mission for the Data Science as a Service (DSaaS) core team is to partner with Segment Data Science teams and IT organizations across The Harford to enable deployment of Data Science assets (data, model, business rules) into business workflows in batch and/or real-time mode. The DSaaS team is responsible for creating playbooks and modular code to enable adoption of best practices within the Data Science organization. Learning from recent deployments using existing architectural patterns, the goal is to evolve the playbook to support the cloud adoption on the AWS platform. The team consults on use cases to provide a high level view of cost, time and effort associated with batch vs real-time implementations. The team is responsible for guiding the Data Science practice to allow for faster, cheaper, consistent, and reliable deployments while enabling transparency and reproducibility of modeling assets.

The Senior Machine Learning Engineer is responsible for hands-on deployments of data science artifacts into business workflows and works closely with the Data Scientists to understand the inputs and outputs of the models. The Senior Machine Learning Engineer will establish logging, error handling, and error recovery criteria to support model failures in production deployments. The engineer will also establish the testing criteria for validating the model deployments in collaboration with the front end engineering teams. The engineer must have an understanding of model deployment pipelines incorporating data from internal systems and third party sources. Expertise in Linux, SQL, Hadoop, and Spark is essential for this role. The engineer should be able to write Python code using object oriented software engineering principles and delivering modularized, reusable code. Understanding of CI/CD tools to automate pipelines and code delivery is preferred.


  • Understand sources of data within The Hartford, and work with SME’s to describe and understand data lineage and suitability for a use case.
  • Create summary statistics/reports from data warehouses, marts, and operational data stores to establish testing criteria and create model training and validation data sets.
  • Produce code artifacts and documentation for reproducibility and hand-off to other data science teams.
  • Contribute to the design, implementation, and evaluation of ML models in production in agile framework. Execute testing (integration, performance, regression).
  • Prototype new approaches and productionize model code to be deployed to business applications
  • Adhere to requirements for scale, performance, and availability
  • Support implementation and testing of assets into production work and manage and estimate work for junior engineers to deliver the requirements for each project.
  • Describe technical work to non-technical audiences.
  • Establish best practices for code management, issue management, data and storage management.
  • Perform code review and mentor engineers on team, set timelines and delivery scope and develop success criteria for project increment delivery.
  • Interact with engineers, architects, product owners, and asset owners to propose a technical solution and provide work estimates to deliver the software. Call out risks and issues and establish escalation criteria for product based on final solution.
  • Provide L3 support for production assets in conjunction with IT production support teams, Data Scientists, and the model Product Owner.
  • Basic knowledge of modeling tools and data science platforms is preferred.
  • Ability to provide input as consultant on projects as a technical expert.
  • Ability to identify and investigate potential data errors during model development or deployment phases.
  • Ability to respond to change, interested in continuous learning, adopting new technologies to enable data science asset deployment into production.
  • Understand tiered application architectures, understand and implement API based predictive and scoring services
  • Establish production support documentation and process with on-shore and off-shore teams.
  • Configure deployments in containerized environments.

Experience & Skills

  • 2+ years of experience in implementing machine learning algorithms (regression, dimensionality reduction, recommendation systems, outlier detection, and predictive models)
  • Experience in leading projects from incubation to large scale production deployments
  • 5+ years’ experience in object oriented programming and design patterns.
  • BA, BS, MS, PHD in Computer Science and Engineering
  • Experience deploying on the AWS platform, certification is preferred but not required.
  • Candidates must have the technical skills to transform, manipulate and store data, the analytical skills to relate the data to the business processes that generates it and the communication skills to disseminate information regarding the availability, quality, and other characteristics of the data to a diverse audience.
  • 3+ years of writing object oriented code in in Python
  • Determine business solutions and translate into actionable steps for self and junior engineers on the team.
  • Demonstrate a passion for learning new skills and creating best practices and standards within the organization.
  • Results oriented with the ability to multi-task and adjust priorities when necessary

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

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

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