Senior / Principal Data Science Engineer

Rwindia; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Rwindia is seeking a Senior / Principal Data Science Engineer in Bengaluru, India, to lead the development of advanced AI and machine learning solutions. This role emphasizes solving complex problems through data analytics and product innovation in the automotive sector.

The ideal candidate will have a robust background in data science, machine learning, and cloud technologies, with a strong emphasis on building scalable AI solutions and advanced analytics platforms.

Qualifications

• Strong experience in Data Science, Machine Learning, and Deep Learning development.
• Expertise in applied AI, machine learning, deep learning, and NLP.
• Strong programming skills in Python and PySpark.

Responsibilities

• Identify business problems and translate them into data-driven analytical solutions.
• Collect, clean, preprocess, and prepare large-scale datasets.
• Build, train, validate, and optimize machine learning models.

Skills

Data Science

Machine Learning

Deep Learning

Python

PySpark

Statistical Modeling

NLP

Big Data Technologies

Cloud Platforms

Microservices Architecture

Education

Bachelor’s or master’s degree in data science, Statistics, Computer Science, or related field

Tools

Spark

Databricks

Azure

Job description

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.