Data Scientist

Job Description

Data Scientist | Koch Industries

The Tone:
This is a full-time role at Koch Industries, located in In-person India (Karnataka). Koch Industries leverages data science, machine learning, and advanced analytics to solve complex business problems across its diverse business functions, aiming to create sustainable value. This role is crucial for developing predictive, forecasting, optimization, and decision-analytics solutions that enable better decision-making and deliver measurable business value throughout the organization. You will own the end-to-end analytics lifecycle, from problem definition to model monitoring, directly influencing business decisions and contributing to solutions that create lasting organizational value.

The TL;DR
• Role: Full Time
• Location: In-person India (Karnataka)
• Team: Collaborative Analytics and AI team focused on delivering end-to-end solutions, partnering closely with business stakeholders, subject matter experts, data engineers, BI professionals, and other AI practitioners.
• Mission: To solve complex business problems, enable better decision-making, and deliver measurable business value through the development of predictive, forecasting, optimization, and decision-analytics solutions.
• Tech Stack: Python (Pandas, NumPy, scikit-learn), SQL, Power BI, Tableau, AWS, Azure

What You’ll Actually Do
• Problem Definition: Translate complex business challenges into well-defined analytical and machine learning problem statements, understanding core needs and potential impacts.
• Model Development: Design, build, validate, and optimize predictive, statistical, forecasting, and machine learning models, developing robust feature engineering strategies and evaluating multiple modeling approaches.
• Data Analysis: Collect, clean, prepare, and analyze structured and unstructured data to uncover actionable insights, performing exploratory data analysis to identify patterns, trends, and opportunities.
• Solution Deployment: Build scalable, reliable, and production-ready analytical solutions, supporting their deployment through APIs, applications, automated pipelines, dashboards, and cloud-based platforms.
• Performance Monitoring & Communication: Monitor model performance, identify data drift, implement continuous improvement processes, and communicate findings, recommendations, and business insights through clear visualizations and compelling narratives.

The Must-Haves
• Background: Bachelor’s or Master’s degree in a quantitative discipline such as Data Science, Statistics, Computer Science, Engineering, Mathematics, or Operations Research.
• Experience: Over 5 years of experience in data science, advanced analytics, or applied machine learning, with a proven track record of developing and deploying scalable, maintainable, and production-ready solutions while working with large, complex, real-world datasets.
• Skills: Strong programming proficiency in Python, including libraries like Pandas, NumPy, and scikit-learn, strong SQL skills for large datasets, hands-on experience with predictive modeling, forecasting, optimization, or advanced statistical analysis, familiarity with data visualization tools (e.g., Power BI, Tableau), and strong communication, collaboration, and stakeholder management abilities to translate analytical results into business recommendations.
• Bonus: Experience deploying machine learning solutions on cloud platforms (AWS or Azure), knowledge of MLOps practices including model versioning and monitoring, exposure to Generative AI, Large Language Models (LLMs), or Retrieval-Augmented Generation (RAG), or experience building end-to-end data products and decision-support systems.