Job Description

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  

• Master's or Ph.D. in Data Science, Machine Learning, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative field.  

• 8+ years of progressive experience in Data Science and Machine Learning roles, with at least 3-5 years in a leadership or principal-level capacity.  

• Demonstrated experience leading multiple end-to-end DS/ML projects successfully from concept to production.  

• Proven track record of managing client interactions, presenting technical solutions, and influencing strategic decisions.  

• Expertise in Python programming (NumPy, Pandas, Scikit-learn, Keras/TensorFlow/PyTorch).  

• Strong understanding of statistical modeling, experimental design, and hypothesis testing.  

• Experience with cloud platforms (AWS, Azure, GCP) and MLOps principles.  

• Excellent communication, interpersonal, and presentation skills.  

Preferred Qualifications  

• Experience with real-time data processing and streaming analytics.  

• Knowledge of various industry verticals and their unique data challenges (e.g., finance, healthcare, retail, logistics, manufacturing).  

• Experience with large-scale data architectures (e.g., data lakes, data warehouses, distributed computing).  

• Publications or presentations in relevant fields.  

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