Data Scientist / ML Engineer / AI Data Engineer

Preferred Hyberabad location

Job Summary:

Seeking a versatile and skilled professional to design, develop, and deploy AI-driven data solutions. This role combines responsibilities across data engineering, data science, and machine learning engineering to deliver actionable insights, scalable ML models, and robust data pipelines that empower business decisions.

Key Responsibilities:

• Design, build, and maintain scalable data pipelines and ETL processes to ingest, process, and store large volumes of structured and unstructured data.
• Develop and optimize machine learning models and AI algorithms tailored to specific business problems.
• Analyze complex datasets to extract actionable insights using statistical methods, data mining, and visualization techniques.
• Collaborate with data scientists, ML engineers, software engineers, and business stakeholders to implement AI solutions.
• Implement data quality and validation frameworks to ensure data integrity and consistency.
• Deploy ML models into production environments, monitor performance, and optimize models for accuracy and efficiency.
• Research and integrate new AI/ML technologies, frameworks, and tools to advance capability and innovation.
• Ensure data security, privacy compliance, and governance standards are met throughout the data lifecycle.
• Document processes, code, and experiments to maintain transparency and reproducibility.

Required Skills and Qualifications:

• Bachelors or Masters degree in Computer Science, Data Science, Engineering, Statistics, or a related field.
• Proficiency in programming languages such as Python, R, or Scala.
• Strong experience with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud platforms (Azure, AWS, GCP).
• Expertise in machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, or MLflow.
• Solid understanding of statistical analysis, data wrangling, and exploratory data analysis (EDA).
• Familiarity with AI techniques including natural language processing (NLP), computer vision, and deep learning.
• Experience with databases and data warehousing solutions (SQL, NoSQL, Redshift, BigQuery).
• Knowledge of containerization and orchestration tools like Docker and Kubernetes.
• Strong problem-solving skills, analytical mindset, and ability to communicate technical concepts effectively.