BlueYonder - Senior Data Scientist

Scope:
- Lead the data science workstream within implementation projects of our newly launched products and ML solutions at first customers in cooperation with Product Management and field teams - Perform data analysis to discover patterns, trends and anomalies in customer data, translate the results into actionable insights, and present results and recommendations to support customers in improving their data quality. - Configure and tune statistical algorithms such as time series and Machine Learning models from open source as well as BY's libraries to support overall project objectives and achieve highest possible quality outcome - Design and build tools and code templates to improve and/or speed up the data science workflow in customer projects to enable scale, leveraging new technologies such as GenAI - Work with BY's Data Scientists, Product Developers, Product Managers and other members of the Blue Yonder team to understand customer-specific requirements and data science related issues and translate them into model enhancement feature requests and tuning options - Collaborate with Data Scientists, Solution Architects and Software Engineers to design and develop tools for the scalable use of AI solutions in supply chain - Write clean, well-structured, documented and efficient (maintainable) code that adheres to software development best practices - Create templates, artifacts, documentation, and training material for the larger data science community, customers and partners towards reusability and automation - Actively and responsively collaborate with the field teams and customers to drive adoption of our new products and services - Communicate and/or support the business cases to PMG and PD regarding specific trends for future product functionality and enhancements - Mentor data science consultants in your own team and/or the wider BY team - Keep up with industry trends in data science practice and continuously improve the team's tools and methodologies

Our current technical environment:
- Software: Python 3-, NumPy, SciPy, scikit-learn, SparkML, pandas, Jupyter Notebook, Matplotlib, Azure ML- Application Architecture: Scalable, Resilient, Reactive, event driven, secure multi-tenant Microservices architecture- Cloud: MS Azure- Frameworks/Others: Snowflake, Kubernetes, Dataflow, Kubeflow, Keras, TensorFlow, PyTorch, FastAPIWhat we are looking for:- Graduate degree in computer science, statistics, or a related quantitative field, is required. PhD is a plus. - 3+ years of demonstrated hands-on experience of script programming languages, preferably Python, with the typical PyData libraries like pandas, scikit-learn, TensorFlow, or pytorch, for data analytics and machine learning applications - 5+ years of experience in software development and/or development of applications in the field of Machine Learning, statistical problem solving, data visualisation or similar - Passion for and advanced knowledge of machine learning and statistical problem solving - Demonstrated experience in building end-to-end data pipelines - Demonstrated experience in building and maintaining the code base with git- Demonstrated experience in bringing ML models into production is preferred - High interest and/or experience in GenAI technologies is preferred - Ability to translate complex data into business insights and opportunities to create value - Ability to communicate analytic insights and recommendations to customers without a deep knowledge of statistics by relating data stories to business situations and processes - Ability to create dashboards, visualizations, and reports to communicate statistical findings - Familiarity with business processes for retail, pricing, and supply chain management is preferred - Demonstrated experience with working with big data and parallel computing - Ready to travel to customer sites based on business needs, and flexible to work with overlapping time zones