Mindex is looking for a Data Science Engineer to be pivotal in building and scaling our data-driven products and services. In this remote role (Req. #748), 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.

What You'll Do

Design and implement scalable data pipelines to ingest, process, and transform large datasets.
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.
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.
Maintain familiarity with leading cloud platforms (AWS, Azure, GCP) for infrastructure management.
Partner with product, engineering, and business teams to translate requirements into technical solutions.

What We're Looking For

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.
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.

Nice to Have

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.

Technical Stack

Languages: Python, SQL
Data Platforms: Databricks, Snowflake, Spark
Orchestration: Airflow, Dagster
Cloud: AWS, Azure, GCP
Deployment: Docker, FastAPI, Flask

Team & Environment

You will join our AI Platform team, collaborating closely to build the foundation for data-driven services.

Benefits & Compensation

Salary: $90,000-$120,000
Comprehensive health, dental, and vision insurance
Employer paid disability, life, and AD&D insurance
401k retirement savings plan with company match
Flexible spending accounts and health savings account with employer contributions
Accident, critical illness, hospital indemnity, and legal assistance
Adoption assistance and domestic partner coverage
Employee assistance program
Paid holidays and flexible time off