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Data Scientist
Data ScientistCoforge • Atlanta, GA, United States
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Data Scientist

Data Scientist

Coforge • Atlanta, GA, United States
1 day ago
Job type
  • Full-time
Job description

Role : Data Scientist

Location : Atlanta, GA

Mode Of Hire : Full Time

Key Responsibilities

  • Data wrangling & feature engineering : Ingest, clean, and transform data from SQL, APIs, and data lakes (e.g., Snowflake, Databricks). Design robust pipelines that feed into analytics and ML workflows.
  • Data understanding & exploration : Work closely with domain experts to deeply understand the meaning, context, quality, and limitations of available datasets. Translate business questions into data requirements and analytics plans.
  • Machine learning development : Build, tune, and validate predictive models using scikit-learn, SparkML, XGBoost, or TensorFlow.
  • Cross-functional partnership : Collaborate with marketing, sales, and product teams to scope business use cases, define success metrics, and integrate models into operational workflows.
  • Model deployment & MLOps : Deploy and manage models using MLflow, docker and CI / CD pipelines. Implement versioning, testing, performance monitoring, and retraining strategies as part of a robust MLOps practice.
  • Infrastructure support : Work with data engineering and DevOps teams to maintain and improve model training and deployment infrastructure, including compute resources, workflow orchestration and environment configuration.
  • Insight delivery : Build clear, actionable reporting and visualizations using tools like Power BI or Tableau. Focus on impact, not just analysis.

Skills Required :

  • Bachelor’s degree in Data Science, Computer Science, Engineering, or a related quantitative field.
  • 5+ years of experience in a data science, ML engineering, or analytics role.
  • Strong SQL, Python and ML Techniques programming skills.
  • Experience with Azure Cloud, Databricks, and / or Snowflake.
  • Experience building and deploying machine learning models in production environments. Hands-on experience with Databricks, including SparkML, and MLflow integration.
  • Familiarity with MLOps best practices, including version control, model monitoring, and automated testing.
  • Experience with tools such as Git, MLflow, Docker and workflow schedulers.
  • Ability to communicate complex technical work to non-technical stakeholders.
  • Experience with scalable model training environments and distributed computing.
  • Preferred Qualifications

  • Master’s degree in a quantitative or technical discipline.
  • Experience in financial services, fintech, or enterprise B2B analytics.
  • Knowledge of A / B testing, causal inference, and statistical experimentation.
  • Familiarity with GenAI, LLM pipelines, and vector-based retrieval is a plus and platform like Snowflake Cortex.
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