Major Duties & Responsibilities • Create Proof of concepts (POCs) / Minimum Viable Products (MVPs), then guide them through to production deployment and operationalization of projects • Influence machine learning strategy for Digital programs and projects • Make solution recommendations that appropriately balance speed to market and analytical soundness • Explore design options to assess efficiency and impact, develop approaches to improve robustness and rigor • Develop analytical / modelling solutions using a variety of commercial and open-source tools (e.g., Python, R, TensorFlow) • Formulate model-based solutions by combining machine learning algorithms with other techniques such as simulations. • Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories. • Create algorithms to extract information from large, multiparametric data sets. • Deploy algorithms to production to identify actionable insights from large databases. • Compare results from various methodologies and recommend optimal techniques. • Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories. • Develop and embed automated processes for predictive model validation, deployment, and implementation • Work on multiple pillars of AI including cognitive engineering, conversational bots, and data science • Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment • Provide guidance and leadership to more junior data scientists, managing processes and flow of work, vetting designs, and mentoring team members to realize their full potential • Lead discussions at peer review and use interpersonal skills to positively influence decision making • Provide thought leadership and subject matter expertise in machine learning techniques, tools, and concepts; make impactful contributions to internal discussions on emerging practices • Facilitate cross-geography sharing of new ideas, learnings, and best-practices Required Qualifications • 7 years of work experience as a Data Scientist • Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL, Hadoop/Hive, Scala) • Good hands-on skills in both feature engineering and hyperparameter optimization • Experience producing high-quality code, tests, documentation • Experience with Microsoft Azure or AWS data management tools such as Azure Data factory, data lake, Azure ML, Synapse, Databricks • Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms, optimization & forecasting techniques, and / or deep learning methodologies • Proficiency in statistical concepts and ML algorithms • Good knowledge of Agile principles and process • Ability to lead, manage, build, and deliver customer business results through data scientists or professional services team • Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis assumptions and results Preferred Qualifications • Experience working in one or multiple supply chain functions (e.g., procurement, planning, manufacturing, quality, logistics) is strongly preferred • Experience in applying AI/ML within a CPG or Healthcare business environment is strongly preferred • Exposure to Pyomo, Mosel, truck load optimization, multi-echelon inventory optimization (MEIO) • Experience in NLP, Vision, and/or AR / VR • • Experience in creating CI/CD pipelines for deployment using Jenkins. • • Experience implementing MLOPs framework along with understanding of data security implementation on ML models • Hands on experience developing ML driven models
