Senior / Principal Data Science Engineer

Job Summary

The Senior / Principal Data Science Engineer is responsible for building advanced AI, Machine Learning, and Big Data solutions that enable data-driven decision-making in product development and automotive business domains. The role focuses on solving complex business problems through advanced analytics, predictive modeling, cloud technologies, and end-to-end AI product development while driving innovation through scalable intelligent systems.

Key Responsibilities

• Partner with stakeholders to identify business problems and translate them into data-driven analytical solutions.
• Collect, clean, preprocess, and prepare large-scale structured and unstructured datasets.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and business insights.
• Build, train, validate, and optimize machine learning and deep learning models.
• Deploy AI/ML models into production environments and continuously monitor performance.
• Develop predictive analytics models for classification, forecasting, anomaly detection, and business intelligence.
• Build AI-powered solutions such as conversational chatbots, NLP/NLU systems, speech recognition, and text-to-speech applications.
• Work on audio/video analytics, facial recognition, eye tracking, and computer vision solutions.
• Design cloud-based scalable microservices architectures for AI applications.
• Utilize big data platforms and tools for processing high-volume, high-velocity, and diverse datasets.
• Collaborate with cross-functional engineering teams in Agile development environments.
• Drive continuous improvement and innovation in advanced analytics and AI solutions.

Required Skills & Experience

• Strong experience in Data Science, Machine Learning, and Deep Learning development.
• Expertise in Applied AI, Machine Learning, Deep Learning, and NLP.
• Strong understanding of machine learning algorithms including Regression, Classification, Clustering, Random Forest, SVM, Naive Bayes, Gradient Boosting, kNN, and Time Series Forecasting.
• Strong expertise in Deep Learning models including ANN, CNN, RNN, and Reinforcement Learning.
• Experience in anomaly detection and predictive modeling techniques.
• Advanced statistical knowledge including Probability Distributions, ANOVA, Hypothesis Testing, Correlation Analysis, ROC, F1 Score, and Statistical Modeling.
• Strong programming skills in Python and PySpark.
• Experience in end-to-end model development, deployment, monitoring, and optimization.
• Knowledge of Big Data technologies and data modeling frameworks.
• Experience in cloud platforms and microservices architecture.
• Strong understanding of AI product development lifecycle and solution architecture.
• Good communication and presentation skills.

Preferred Qualifications

• Bachelor’s or master’s degree in data science, Statistics, Computer Science, or related field.
• Experience with Spark, Databricks, and Azure technology stack.
• Experience with cloud or on-premise model deployment.
• Experience building enterprise AI products or advanced analytics platforms.

Other Requirements

• Strong analytical and mathematical problem-solving skills.
• Ability to work independently or in small high-performing teams.
• Strong business understanding and ability to align technical solutions with business strategy.