Overview of the Role

We are seeking a Lead Data Science Engineer with over a decade of experience in developing and deploying advanced data science solutions. This role blends hands-on technical expertise with leadership responsibilities. You will guide a team of 5–6 engineers, collaborate directly with customers, and ensure that research ideas are translated into scalable, production-ready systems. The ideal candidate will possess strong skills in machine learning, statistical modeling, and data engineering, as well as the ability to drive strategic direction for data initiatives.

Roles and Responsibilities

• Design, develop, and deploy machine learning and AI models that deliver measurable business value.
• Lead a team of data science engineers, providing mentorship, technical guidance, and performance oversight.
• Work on time series forecasting models for IoT sensor data using both traditional (ARIMA, SARIMA) and deep learning approaches (RNN, LSTM, GRU).
• Build, train, and optimize models for recommendations, predictions, and prescriptive analytics using production datasets.
• Develop and deploy NLP and computer vision solutions for real-world applications.
• Explore and implement LLM and SLM capabilities using frameworks such as LangChain, LangGraph, and HuggingFace.
• Collaborate with data engineering teams to ensure seamless data pipelines and infrastructure readiness.
• Interact with customers to understand requirements, present solutions, and drive stakeholder alignment.
• Ensure scalability, reliability, and robustness of AI/ML models in production environments.

Desired Skills/Background

• Bachelor’s or Master’s degree in Computer Science, with certification in AI/ML.
• 5+ years of industry experience in data science and engineering.
• Strong programming and debugging skills in Python, with expertise in key AI/ML packages.
• Proven expertise in data mining, pattern analysis, and anomaly detection techniques.
• Hands-on experience in building and deploying time series forecasting models for IoT data.
• Solid background in training and deploying ML models for recommendation, prediction, and prescription tasks.
• Working knowledge of NLP, computer vision, and modern LLM/SLM solutions.
• Practical experience with cloud platforms and data engineering tools.
• Strong communication skills with the ability to manage client discussions and team deliverables.
• Demonstrated ability to lead small technical teams and drive projects to completion.