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Title: Machine Learning/Data science Engineer
Location: Cincinnati, OH 45202 (onsite)
Duration: 12 Months Contract
Must Have: ETL, Python, SQL
Nice To Have: AWS SageMaker, DBT, Snowflake
Job Description
Squad: Machine Learning Data Enablement squad in the Data Insights Tribe
Title: Machine Learning/Data science Engineer
Location: Cincinnati, OH 45202 (onsite)
Duration: 12 Months Contract
Must Have: ETL, Python, SQL
Nice To Have: AWS SageMaker, DBT, Snowflake
Job Description
Squad: Machine Learning Data Enablement squad in the Data Insights Tribe
- We’re hiring a Data Engineer to join our newly launched Machine Learning Data Enablement team at client. This team is focused on building high-quality, scalable data pipelines that power machine learning models across the enterprise, deployed in AWS SageMaker.
- We’re looking for an early-career professional who’s excited to grow in a hands-on data engineering role. Ideal candidates will have experience working on machine learning–related projects or have partnered with data science teams to support model development and deployment — and have a strong interest in enabling ML workflows through robust data infrastructure.
- You’ll work closely with data scientists and ML engineers to deliver curated, production-ready datasets and help shape how machine learning data is delivered across the bank. You should have solid SQL and Python skills, a collaborative mindset, and a strong interest in modern data tooling. Experience with Snowflake, dbt, or cloud data platforms is a strong plus. Familiarity with ML tools like SageMaker or Databricks is helpful but not required — we’re happy to help you learn.
- This is a hands-on role with high visibility and high impact. You’ll be joining a team at the ground level, helping to define how data powers machine learning at scale.