Lead Data Scientist

Lead technical roadmap and delivery of ML and GenAI capabilities for retail pricing, demand forecasting, promotion effectiveness, and markdown recommendations. Architect GenAI agents and set model/MLOps standards, mentor distributed data science teams, partner with product and engineering, and present AI strategy to executives and customers. The summary above was generated by AI

DemandTec is a retail analytics and demand science platform used by grocery retailers and CPG suppliers to run pricing, promotions, markdowns, and trade fund decisions on connected, AI-powered intelligence rather than siloed point solutions. Backed by Longshore Capital, we’re modernizing a market-leading core into an AI/ML-native, composable platform - with a live network of 7,800+ connected CPG suppliers, the largest and hardest-to-replicate asset in the category.

We’re building the next generation of our solution platform for retail and analytics: GenAI-powered agents, real-time decisioning, and connected optimization across pricing, promotions, markdowns, and trade funds. This team sits at the center of that build., * Own the technical roadmap for ML/AI models powering price optimization, demand forecasting, promotion effectiveness, and markdown recommendations.

• Architect and lead development of GenAI-powered agents and copilots (e.g., pricing copilots, demand intelligence agents) in partnership with engineering and product.

• Set technical standards for model development, validation, and MLOps across the data science organization.

• Mentor, coach, and grow a distributed team of data scientists, including direct oversight of the China and Poland-based team.

• Partner with product and engineering leadership to translate retail and trade-promotion business problems into Data Science solutions.

• Make build-vs-buy calls on LLM/GenAI tooling and vendor platforms together with ENG.

• Present model performance, technical roadmap, and AI strategy to executive leadership and, where relevant, customers and prospects.

• Track emerging AI/ML techniques and assess their applicability to retail and CPG use cases., Artificial Intelligence * Automotive * Computer Vision * Information Technology * Internet of Things * Logistics * Software Lead the evaluation and data-quality strategy for advanced AI, vision, and perception systems. Define metrics, failure taxonomies, and human-review protocols; translate evaluation findings into data strategy, experiment priorities, and product release decisions. Partner with model, simulation, and platform teams to drive production-readiness and continuous quality improvements. Top Skills: Computer VisionDataset DesignDeep LearningGenerative AiGeospatial AiModel EvaluationMultimodal AiObject DetectionPerception SystemsSegmentationSimulationSynthetic Data EvaluationTemporal ConsistencyVideo Quality Metrics Forward Financing, Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

• 7+ years of experience in data science or applied ML, including 2+ years leading data scientists or a technical team.

• Proven track record shipping production ML models at scale.

• Experience designing, building, and shipping models for price elasticity, demand forecasting, promotion effectiveness, and similar retail/CPG use cases.

• Strong communication skills - able to translate technical work into business impact for executives and customers.

Technical Skills

• Proficiency in Python, SQL, and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).

• Familiarity with GenAI frameworks (e.g., LLMs, Dify, LangChain, RAG pipelines).

• Familiarity with cloud-based data platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Hadoop, Databricks).

• Experience with data visualization tools (e.g., Power BI, Tableau) and modern MLOps practices.

Senior level Senior level Security Lead development, validation, deployment, and quality control of advanced analytics and ML solutions for fraud detection, waste and abuse, investigative analysis, and program integrity. Provide technical leadership, translate stakeholder requirements, mentor team members, and ensure models are explainable, defensible, and production-ready. Top Skills: PythonRSQL

What you need to know about the Colorado Tech Scene

With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.

Key Facts About Colorado Tech

• Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
• Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
• Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
• Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
• Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
• Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute