Senior Data Scientist - Python, Spark, Machine Learning, AWS, SQL, Big Data ETL, NLP, GenAI

No third-party candidates

Introduction:

We are seeking a highly skilled Senior Data Scientist with expertise in Python, Spark, Machine Learning, AWS, SQL, Big Data ETL, NLP, and Generative AI. The selected candidate will be responsible for designing and implementing advanced analytics and machine learning solutions, focusing on building scalable data pipelines, developing predictive models, and delivering data-driven insights using modern data science techniques.

Responsibilities:

• Lead the end-to-end machine learning lifecycle including problem framing, feature engineering, model development, validation, deployment, and monitoring.
• Develop and optimize machine learning models including supervised learning, unsupervised learning, statistical modeling, and forecasting.
• Build scalable ETL pipelines using Spark for large-scale data processing.
• Conduct exploratory data analysis (EDA) to identify trends and insights from large datasets.
• Develop anomaly detection, predictive analytics, and risk scoring models.
• Implement NLP and Generative AI techniques for automation and data insights.
• Design feature engineering pipelines for real-time and batch machine learning workloads.
• Integrate data from APIs, relational databases, flat files, and distributed data systems.
• Work with engineering teams to deploy models using MLOps best practices.
• Communicate analytical insights and model outcomes to both technical and non-technical stakeholders.
• Mentor junior data scientists and contribute to data science best practices.

Requirements:

• Strong programming experience with Python for data science and machine learning.
• Hands-on experience with Apache Spark for distributed data processing.
• Advanced knowledge of machine learning algorithms and statistical modeling techniques.
• Experience designing and maintaining scalable ETL pipelines.
• Strong SQL skills and experience working with relational and NoSQL databases.
• Experience working with large-scale Big Data environments.
• Strong understanding of data preprocessing, feature engineering, and exploratory data analysis.

Preferred Skills:

• Experience with Generative AI, NLP, and large language models.
• Experience with AWS services such as S3, EMR, Glue, Lambda, and SageMaker.
• Knowledge of MLOps tools and model deployment pipelines.
• Experience with deep learning frameworks.
• Familiarity with Linux environments.

Experience Required:

• Minimum 8+ years of experience in Data Science, Machine Learning, or related roles.
• Strong experience working with Python, Spark, AWS, and Big Data environments.