Data Scientist

Job Title: Data Scientist

Location: Columbus, OH (Hybrid)

Contract: W2 Only (NO C2C/1099)

Duration: 12+ Months

Job Summary:

We are seeking an innovative and analytical Data Scientist to join our team. The ideal candidate will have strong experience in data visualization, data warehousing, data governance, and advanced machine learning techniques, including Generative AI. You will work on transforming complex datasets into actionable insights and building intelligent solutions that drive business growth.

Key Responsibilities:

• Collect, clean, and preprocess large datasets from multiple sources.
• Design and implement data visualization dashboards using tools like Power BI, Tableau, or Looker.
• Develop and maintain data pipelines and integrate with data warehouses (Snowflake, Redshift, BigQuery).
• Ensure compliance with data governance policies, security standards, and regulatory requirements.
• Build and deploy machine learning models for predictive analytics and optimization.
• Research and implement Generative AI models (LLMs, diffusion models) for innovative business use cases.
• Collaborate with cross-functional teams to understand requirements and deliver data-driven solutions.
• Monitor model performance and continuously improve algorithms.
• Document processes and maintain reproducibility of data science workflows.

Required Skills & Qualifications:

• 12+ years of experience in data science and analytics.
• Strong proficiency in Python, R, and ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with data visualization tools (Power BI, Tableau).
• Solid understanding of data warehousing concepts and SQL.
• Knowledge of data governance frameworks and compliance standards.
• Experience with cloud platforms (AWS, Azure, Google Cloud Platform) and their data services.
• Excellent problem-solving and communication skills.

Preferred Qualifications:

• Experience with Generative AI (LLMs, GPT-based models, diffusion models).
• Familiarity with MLOps tools and practices.
• Exposure to big data technologies (Spark, Hadoop).
• Contributions to open-source AI/ML projects or published research.