As a Data Scientist, you will solve complex business problems using data science, machine learning, and advanced analytics. In this role, you will own the end-to-end analytics lifecycle, from problem definition and data exploration through model development, deployment, and performance monitoring. You will work closely with business stakeholders, data engineers, and analytics professionals to build scalable, production-ready solutions that drive meaningful outcomes. While exposure to Generative AI technologies is beneficial, strong foundations in statistics, machine learning, and applied data science are essential for success.
You will join a collaborative Analytics and AI team focused on delivering end-to-end solutions across multiple business functions. Our team partners closely with business stakeholders, subject matter experts, data engineers, BI professionals, and AI practitioners to solve high-value business challenges.
Translate business challenges into well-defined analytical and machine learning problem statements.
Collect, clean, prepare, and analyze structured and unstructured data to uncover actionable insights.
Perform exploratory data analysis (EDA) to identify patterns, trends, and opportunities.
Design, build, validate, and optimize predictive, statistical, forecasting, and machine learning models.
Assess model performance using appropriate statistical and business metrics.
Support solution deployment through APIs, applications, automated pipelines, dashboards, and cloud-based platforms.
Monitor model performance, identify data drift, and implement continuous improvement processes.
Document methodologies, assumptions, data sources, and model performance to support governance, transparency, and reuse.
Bachelor's or Master's degree in Data Science, Statistics, Computer Science,



Engineering, Mathematics, Operations Research, or a related quantitative discipline.

- 5+ years of experience in data science, advanced analytics, or applied machine learning.
- Strong programming experience in Python, including libraries such as Pandas, NumPy, scikit-learn, and statistical modeling packages.
- Strong SQL skills and experience working with structured and large-scale datasets.
- Hands-on experience with predictive modeling, forecasting, optimization, or advanced statistical analysis.
- Experience developing and deploying scalable, maintainable, and production-ready solutions.
- Experience working with large, complex, real-world datasets.
- Familiarity with data visualization tools such as Power BI, Tableau, or similar platforms.
- Experience deploying machine learning solutions on cloud platforms such as AWS or Azure.

Experience with time-series forecasting, optimization techniques, and advanced statistical modeling.
Knowledge of MLOps practices including model versioning, monitoring, CI/CD pipelines, and automated retraining.
Exposure to Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI-assisted analytics solutions.
Experience building end-to-end data products and decision-support systems.
Background in engineering, applied statistics, operations research, or related quantitative disciplines.
Experience influencing business decisions through data-driven insights and scalable analytical solutions.
Any compensation range provided for a role is an estimate determined by available market data. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy.
We seek to enable the best work workplace that helps you and the business work together to produce superior results.

📌 Data Scientist (Python, ML, SQL) (Bengaluru)
🏢 Koch Business Solutions Asia Pacific Pte.
📍 Bengaluru