Sr. Principal Data Scientist / Machine Learning Engineer

Job Summary

We're looking for an exceptionally skilled and experienced Sr. Principal Data Scientist / Machine Learning Engineer to lead and deliver high-impact AI / ML projects across Automotive domain. The ideal candidate will have a deep understanding of data science and machine learning tools, techniques, and algorithms, coupled with a proven track record of successfully leading projects from conception to deployment. This role demands strong client-facing communication skills and the ability to translate complex technical concepts into tangible business value.

Key Responsibilities

• Technical Leadership & Strategy :
• Serve as a primary technical expert and thought leader in Data Science and Machine Learning.
• Define and drive the technical strategy for AI / ML initiatives, identifying high-value opportunities for optimization, predictive analytics, and process improvement across diverse use cases.
• Architect and oversee the development of robust, scalable, and production-ready DS / ML models and solutions.
• Stay at the forefront of the latest advancements in DS / ML, especially those applicable to various industries and large-scale data problems.
• Project Leadership & Delivery :
• Lead end-to-end DS / ML projects, including requirements gathering, data exploration, model development, validation, deployment, and monitoring.
• Define project scope, timelines, and deliverables, ensuring successful execution within budget and schedule constraints.
• Mentor and guide junior and mid-level data scientists and ML engineers, fostering a culture of technical excellence and continuous learning.
• Drive MLOps best practices for reliable and efficient model deployment and lifecycle management.
• Client Management & Communication :
• Act as a trusted advisor to clients and internal stakeholders, understanding their business challenges and translating them into solvable DS / ML problems.
• Effectively communicate complex analytical findings, model performance, and business recommendations to both technical and non-technical audiences.
• Manage client expectations, present progress reports, and ensure stakeholder satisfaction.
• Facilitate workshops and discovery sessions to identify new opportunities for AI / ML adoption.
• Use Case Development & Problem Solving :
• Lead the identification, prioritization, and execution of complex AI / ML use cases that drive significant business impact.
• Apply deep analytical skills to dissect complex problems, derive actionable insights from data, and design innovative solutions.
• Develop and implement models for :
• Predictive Analytics : Forecasting, risk assessment, and anomaly detection.
• Optimization : Improving efficiency, resource allocation, and decision-making.
• Pattern Recognition : Identifying trends, segments, and relationships within large datasets.
• Automation : Leveraging ML for intelligent process automation and enhanced operational efficiency.
• Tool & Algorithm Proficiency :
• Demonstrated expertise in a wide range of DS / ML tools and platforms (e.g., Python, R, TensorFlow, PyTorch, scikit-learn, Spark, AWS Sagemaker, Azure ML).
• Deep understanding and practical application of various machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning, deep learning, time series analysis, NLP, computer vision).
• Proficiency in data manipulation, SQL, and working with large, complex datasets from various sources.

Qualifications

Preferred Qualifications