Data Scientist

Key Responsibilities

• Lead end-to-end data science projects from problem definition to production deployment.
• Design, develop, validate, and optimize machine learning and predictive models.
• Build scalable ETL/data pipelines using PySpark, Databricks, and Delta Lake.
• Perform statistical analysis, feature engineering, forecasting, and predictive analytics.
• Implement MLOps best practices using MLflow, CI/CD pipelines, and model monitoring tools.
• Optimize Spark workloads for scalability, performance, and cost efficiency.
• Work with AWS services including S3, Glue, IAM, Redshift, and cloud-native analytics tools.
• Collaborate with data engineers, architects, product owners, and business stakeholders.
• Translate business requirements into analytical solutions and actionable insights.
• Ensure data quality, governance, and security across cloud environments.
• Conduct experimentation, A/B testing, and model performance evaluation.
• Mentor junior team members and participate in code/model reviews.
• Maintain technical documentation and contribute to knowledge sharing initiatives.
• Stay updated with the latest advancements in AI/ML, cloud computing, and data engineering.

Required Skills

• Strong experience in Python for Data Science and Machine Learning.
• Hands-on expertise with Spark, PySpark, and Spark MLlib.
• Experience with Databricks and Delta Lake.
• Strong understanding of machine learning algorithms and statistical modeling.
• Experience implementing MLOps using MLflow and CI/CD pipelines.
• Expertise in AWS cloud services such as S3, Glue, IAM, and Redshift.
• Experience with predictive modeling, feature engineering, and model evaluation.
• Strong SQL and data processing skills.
• Excellent problem-solving and communication skills.

Preferred Qualifications

• Experience with large-scale distributed data processing.
• Knowledge of NLP, Deep Learning, or Generative AI is a plus.
• Experience with Docker, Kubernetes, or workflow orchestration tools is preferred.
• Prior experience in mentoring or leading data science teams.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law.