Data Science Engineer

6 days ago


Austin, Texas, United States Habitat Energy Full time
About Habitat Energy

Habitat Energy is a pioneering technology company dedicated to optimizing energy storage and renewable assets worldwide. Our mission is to deliver exceptional returns to clients, making renewable energy more attractive globally and supporting the transition to a clean energy future.

With a team of over 90 professionals across three global offices – Austin, TX, Oxford, UK, and Melbourne, Australia – we bring together experts in energy trading, data science, software engineering, and renewable energy management.

Job Description

We are seeking a highly skilled Machine Learning Ops Engineer to join our US team based in Austin, TX. This role will be embedded with the Data Science team to develop model workflows, provide support and improvements, and manage data flow through our system.

  • Develop efficient Python code that transforms optimization or machine learning prototypes into production-grade solutions.
  • Maintain/improve models, mentor, and support coding practices within the Data Science team.
  • Contribute to designing, developing, implementing, and improving data engineering tools, workflows, processes, and platforms.
  • Assist in backtesting and model tuning frameworks development and maintenance.
  • Enhance data quality across accuracy, availability, performance, and accessibility dimensions.
Requirements
  • 3+ years of Python experience.
  • 3+ years of working with data scientists/ML researchers to develop tooling, collaborate on backtesting frameworks, build data pipelines, build/maintain orchestration workflows, or productionize code.
  • Proficiency in Orchestration and IaC (Airflow, ECS, Kubernetes, Terraform, CloudFormation), Git, Containerization (docker), SQL (Postgres, Snowflake).
Benefits

Competitive salary, flexible working arrangements, and numerous personal development opportunities await you at Habitat Energy. We operate a hybrid working model with at least 2 days in our offices in Austin, Texas.



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