Key Responsibilities

• Collect, process, and analyze large volumes of structured and unstructured data from various sources.
• Develop and deploy machine learning models and algorithms for predictive analytics, classification, clustering, etc.
• Design data pipelines and ETL processes to automate data flow.
• Collaborate with data engineers and software developers to implement scalable data architectures.
• Interpret model results, visualize insights, and communicate findings to stakeholders.
• Monitor model performance and retrain models as necessary.
• Ensure data quality, integrity, and compliance with data governance standards.
  
  

Required Skills

• Strong proficiency in Python/R and SQL.
• Hands-on experience with ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Experience with big data tools and platforms like Spark, Hadoop, or Databricks.
• Solid understanding of statistics, data mining, and data wrangling techniques.
• Familiarity with cloud services (AWS, GCP, Azure) and MLOps tools.
• Knowledge of version control (Git) and deployment strategies.