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Data Science Engineer - Remote; Req

Remote / Online - Candidates ideally in
City of Rochester, Rochester, Monroe County, New York, 14602, USA
Listing for: Mindex
Remote/Work from Home position
Listed on 2026-01-02
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Data Science Engineer - Remote (Req. #748)
Location: City of Rochester

Founded in 1994 and celebrating 30 years in business, Mindex is a software development company with a rich history of demonstrated software and product development success. We specialize in agile software development, cloud professional services, and creating our own innovative products. We are proud to be recognized as the #1 Software Developer in the 2023 RBJ's Book of Lists and ranked 27th in Rochester Chamber’s Top 100 Companies.

Additionally, we have maintained our certification as a Great Place to Work for consecutive years in a row. Our list of satisfied clients and #ROCstar employees are both rapidly growing— Are you next to join our team?

Mindex’s Software Development division is the go-to software developer for enterprise organizations looking to engage teams of skilled technical resources to help them plan, navigate, and execute through the full software development lifecycle.

We are seeking a highly skilled and motivated Data Science Engineer to join our AI Platform team.

Essential Functions

This role will be pivotal in building and scaling our data-driven products and services. You will transform raw data into actionable intelligence, develop and deploy robust machine learning models, and help establish foundational MLOps workflows on modern cloud infrastructure.

Key Responsibilities
  • Design and implement scalable data pipelines to ingest, process, and transform large datasets (structured & unstructured).
  • Develop, validate, and optimize supervised and unsupervised machine learning models leveraging Python, SQL, and modern libraries.
  • Conduct feature engineering, model selection, and statistical modeling to deliver high-impact solutions.
  • Build and expose model APIs or containerized workflows for seamless integration and deployment in production environments.
  • Apply MLOps best practices to model versioning, testing, monitoring, and deployment.
  • Work with Big Data technologies such as Databricks and Snowflake to unlock analytics at scale.
  • Orchestrate complex workflows using tools like Airflow or Dagster for automation and reliability.
  • Collaborate with AI teams to refine prompt engineering and leverage AI tooling for model fine-tuning and augmentation.
  • Maintain familiarity with leading cloud platforms (AWS, Azure, GCP) for model training, deployment, and infrastructure management.
  • Partner with product, engineering, and business teams to translate requirements into technical solutions.
Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, or a related field.
  • 3+ years of experience in data science engineering or related roles.
  • Proficiency in Python and SQL for data extraction, analysis, and modeling.
  • Strong background in statistical modeling and machine learning algorithms (supervised and unsupervised).
  • Experience with feature engineering and end-to-end model development.
  • Hands‑on experience with MLOps foundations (CI/CD, model monitoring, automated retraining).
  • Familiarity with Big Data tools (Databricks, Snowflake, Spark).
  • Experience with workflow orchestration platforms such as Airflow or Dagster.
  • Understanding of cloud architecture and deployment (AWS, Azure, GCP).
  • Experience deploying models as APIs or containers (Docker, FastAPI, Flask).
  • Familiarity with prompt engineering techniques and AI tooling for cutting‑edge model development.
  • Excellent problem‑solving and communication skills.
Preferred
  • Experience with advanced AI tools (e.g., LLMs, vector databases).
  • Exposure to data visualization tools and dashboarding.
  • Knowledge of security, privacy, and compliance in ML workflows.
Physical Conditions/Requirements
  • Prolonged periods sitting at a desk and working on a computer.
  • No heavy lifting is expected. Exertion of up to 10 lbs.
Benefits
  • Health insurance
  • Paid holidays
  • Flexible time off
  • 401k retirement savings plan and company match with pre‑tax and ROTH options
  • Dental insurance
  • Vision insurance
  • Employer paid disability insurance
  • Life insurance and AD&D insurance
  • Employee assistance program
  • Flexible spending accounts
  • Health savings account with employer contributions
  • Accident, critical illness, hospital indemnity, and legal assistance
  • Adoption assistance
  • Domestic partner coverage
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