Data Science Consultant – Machine Learning, Advanced Analytics, Python, SQL

. Onboard clients onto Blue Yonder’s Luminate Planning suite of solutions and provide ongoing support .

Posted 10/15/2026full-timeBangalore • IndiaMid-LevelSeniorWebsite

Tools & technologies

NumpyPandasPythonSQL

Key responsibilities & impact

Onboard clients onto Blue Yonder’s Luminate Planning suite of solutions and provide ongoing support
Select features, build, evaluate, and optimize classifiers using advanced machine-learning techniques
Conduct data mining using state-of-the-art methods, frameworks, and tools
Integrate third-party data sources to enhance company datasets when required
Refine data-collection procedures to ensure relevant, reliable information is available for analytical systems
Process, cleanse, transform, and verify the integrity of data used for analysis
Perform ad hoc analysis and present findings clearly to technical and business stakeholders
Address customer concerns related to forecasting issues and data quality
Build reusable utilities for forecasting checks and validation
Write maintainable scripts and analytical code, and support API-based and workflow integrations where applicable
Mentor junior team members, provide technical guidance, and contribute to team capability development
Collaborate with implementation, product, support, and customer teams to deliver effective onboarding and ongoing support

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, Operations Research, or a related discipline, with a focus on data science or analytics
5-7 years of relevant experience in data science, machine learning, advanced analytics, or a closely related field
Solid understanding of machine-learning algorithms, including Linear Regression, K-Means Clustering, and Naive Bayes
Proficiency in data-science toolkits such as Python, NumPy, Pandas, Matplotlib, and Seaborn, with strong hands-on expertise in at least two
Experience with supply-chain concepts and statistical analysis
Knowledge of operations research concepts, including integer, linear, and stochastic programming
Solid grounding in applied statistics, including probability distributions, hypothesis testing, and regression analysis
Proficiency in query technologies such as SQL and Snowflake, or Python-based SQL wrappers
Familiarity with data-visualization and application tools such as Streamlit and Power BI
Strong scripting and programming capability, with a data-driven mindset and close attention to detail
Strong critical thinking, operational thinking, communication, leadership, and stakeholder-management skills
Ability to work effectively in a global environment and mentor junior team members