Jobs via Dice
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
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.
Seniority Level Entry level
Employment Type Full-time
Job Function Information Technology
Industries Software Development
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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
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.
Seniority Level Entry level
Employment Type Full-time
Job Function Information Technology
Industries Software Development
#J-18808-Ljbffr