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

Scope   As a Data Science Consultant, you will be a key player in onboarding clients onto Blue Yonder’s Luminate Planning suite of solutions and providing ongoing support . Our team currently consists of approximately 50 associates in India, as part of a larger global team spanning the United States and Germany, and is poised for rapid growth. Strong communication and leadership abilities are essential, as you will mentor junior team members and collaborate with global, cross-functional stakeholders.   What you'll do   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, and 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 we are looking for

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.

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All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.