Analyze large and complex datasets to identify trends, patterns, and actionable insights; develop and implement machine learning models and algorithms; collaborate with cross-functional teams; design and maintain scalable data pipelines; communicate findings and recommendations; stay updated on latest advancements; ensure data quality, integrity, and security; optimize and fine-tune models for performance and scalability.
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Compensation
Competitive salary and performance-based bonuses.
Responsibilities
Analyze large and complex datasets to identify trends, patterns, and actionable insights.
Develop and implement machine learning models and algorithms to solve business challenges.
Collaborate with cross-functional teams to understand business objectives and translate them into data-driven solutions.
Design and maintain scalable data pipelines and workflows for data collection, processing, and analysis.
Communicate findings and recommendations to stakeholders through clear visualizations and reports.
Requirements
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
Developing innovative data products and implementing automation, advanced AI/ML, and Generative AI capabilities to drive business value through demand forecasting and analytics.
Responsibilities
Develop and maintain high-accuracy short-term and long-term demand forecasts at Automotive Segmentation and Powertrain levels.
Build, validate, and deploy time-series models (e.g. ARIMA) and ML algorithms to identify market trends.
Proactively integrate Generative AI / Agentic AI and other modern AI tools into daily workflows.
Act as a strategic partner to Sales, Marketing and Finance teams, translating analytical outputs into clear business recommendations.
Lead monthly forecasting reviews, presenting findings to senior stakeholders.
Lead data science initiatives for Blue Yonder’s Applied Data Science team, driving product adoption, forecasting, planning, and pricing improvements for customers.
Responsibilities
Select, build, and optimize classifiers using advanced machine learning techniques.
Conduct data mining using cutting-edge methods and tools.
Integrate third-party data sources to enhance the company’s datasets when necessary.
Refine data collection procedures to ensure relevant data is available for analytic systems.
Process, cleanse, and verify the integrity of data used for analysis.
Requirements
Bachelor’s or master’s degree in computer science with a focus on Data Science
Develop Python applications, quantitative tools and data infrastructure to support trading decisions, research and risk management in the commodities space.
Responsibilities
Design, develop and deploy quantitative tools supporting trading and research, including pricing, backtesting, risk analysis and PnL reporting
Build Python applications and data pipelines to explore, integrate and analyse alternative datasets, including weather and cargo data
Collaborate with Quantitative Researchers and Traders to translate trading ideas and business requirements into production applications and quantitative models
Architect, develop and maintain cloud applications in collaboration with infrastructure engineers, using AWS and related technologies
Develop and apply statistical and machine learning models to support research and trading across Agriculture, Metals and Energy
Requirements
Nice to have: advanced AWS experience
Nice to have: Snowflake experience
Nice to have: parallel or distributed computing
Nice to have: statistical or machine learning models
Nice to have: mentoring junior developers or interns
Modeler to develop and analyze complex dynamic systems for national security, healthcare, and transportation domains.
Compensation
$98,800 - $123,500 - $148,200 Annual
Responsibilities
Formulate and develop models and simulations of real world problems involving complex dynamic systems
Develop research questions and test hypotheses with open ended tasking
Work with government sponsors to evaluate solutions and conduct analyses
Support development and application of analytic models
Present results intuitively and actionably
Requirements
Master's degree in quantitative field such as Data Science, Computational Social Science, Mathematics, Statistics, Operations Research, Geospatial Science, Computer Science, Software Engineering, Economics
