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MLOps Engineer
Hastings DirectMLOps Engineer productionising machine-learning models and pipelines for Hastings Direct, a UK digital insurance provider. Improving testing, deployment, monitoring and governance across pricing workflows.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates strong capabilities in building and maintaining machine learning pipelines, with a focus on Python programming, SQL proficiency, and MLOps practices. Emphasizes collaboration with cross-functional teams and a commitment to quality, reliability, and governance in data workflows.
Highest-signal resume keywords
Python ProgrammingSQL ProficiencyMLOps PracticesGit and Code ReviewCloud-Based Environments
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine Learning WorkflowsData Pipeline DevelopmentModel DeploymentTesting and DocumentationAutomated Workflows
Soft Skills
Problem-SolvingAttention to DetailClear Communication
Tools & Technologies
AzureAWSGCPSnowflakeDatabricksSparkAirflowMLflowAzure DevOpsGitHub Actions
Industry Keywords
PricingInsuranceFinancial ServicesModel GovernanceResponsible AI
Tech Stack
Tools & technologiesAirflowAWSAzureCloudGoogle Cloud PlatformPythonSparkSQL
About the role
Key responsibilities & impact- Build, improve and maintain machine learning pipelines used within Market Pricing
- Productionise Python-based models, notebooks and data science workflows
- Move models from development into repeatable, tested and documented production processes
- Improve testing, release, monitoring and maintenance of model workflows
- Investigate issues across data, model and pipeline workflows
- Automate manual steps to improve quality, speed or control
- Support Git, code review, testing and documentation practices
- Ensure pipelines and model workflows are traceable, auditable and safe to change
- Collaborate with Pricing, Data Science, Data Engineering, ML Engineering and governance stakeholders
- Own defined MLOps components and pipelines while contributing to standards, architecture and governance
Requirements
What you’ll need- Strong Python skills and experience building data or machine learning workflows
- Good SQL skills and confidence working with structured datasets
- Experience building reliable, reusable and maintainable code or pipelines
- Understanding of machine learning fundamentals, especially supervised learning
- Experience with Git, code review, testing and technical documentation
- Exposure to cloud-based data or engineering environments
- Good problem-solving skills and attention to detail
- Clear communication skills and ability to explain technical ideas to different audiences
- Comfortable working with data scientists, analysts, engineers and business stakeholders
- Practical focus on quality, reliability, governance and maintainability
- Hands-on experience with Azure, AWS or GCP is nice to have
- Exposure to Snowflake, Databricks, Spark or similar is nice to have
- Experience with MLOps practices such as model deployment, monitoring, versioning or model registries is nice to have
- Exposure to Airflow, MLflow, Azure DevOps, GitHub Actions or similar is nice to have
- Experience in pricing, insurance, financial services or another regulated environment is nice to have
- Understanding of model governance, responsible AI or explainability is nice to have
- Must be able to complete the employer's thorough referencing process, including credit and criminal record checks
- Employer is unable to offer sponsorship for this position
Benefits
Comp & perks- Flexible working – flexible hybrid working approach
- Competitive bonus scheme – annual 4Cs performance bonus
- Life assurance cover at 4x salary
- Income protection at no extra cost
- Matched pension contributions up to 10%
- Discounts and cashback
- Free independent mortgage advice
- Free access to financial wellbeing support
- Thrive mental health app
- 24/7 colleague assistance programme
- In-house mental health first aiders
- Support groups and dedicated wellbeing team
- 25 days annual leave plus bank holidays
- Option to buy or sell one week of annual leave
- Health care cash back plans
- Dental plans
- Discounted health assessments
- Cycle to work scheme
- Tech schemes
- Discounted and free onsite facilities
- Social events throughout the year
- Support, training and development