Senior Data Scientist

Job not on LinkedIn

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🇺🇸 United States – Remote

💵 $160k - $170k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

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.Kreate

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1997

💼 Consulting

📦 Logistics

⚡ Energy

Consulting • Logistics • Energy

Kreate is an India-based energy technology and trading company that combines power trading, renewable energy services, and software products. It operates as a registered trading and clearing member of Indian Energy Exchange (IEX) and Power Exchange India Limited (PXIL), facilitating short- and long-term power sale/purchase, open access transactions, and Renewable Energy Certificate (REC) trading. The company develops AI/ML and statistics-driven forecasting and analytics platforms (e. g. , RED Fx) for accurate renewable generation and demand forecasts, and offers a suite of energy-focused software products including trading, scheduling, energy accounting, real-time monitoring (RealGen), and EMS solutions. . Kreate serves utilities, generators, industrial and commercial clients and is organized into divisions such as Kreate Technologies, Kreate Energy, Kreate Lights, and Kreate Commodity.

📋 Description

• Own the production planning model, including demand forecasting, safety stock and inventory targets, and forward production plans across plants • Build capacity and scheduling optimization models, including press and mold assignment, site balancing, and utilization targets while accounting for tool availability • Own metric governance and establish consistent definitions for key business metrics, including labor as a percentage of production sales value, OEE, and net sales • Reconcile metric definitions and calculations across the lake house, Power BI, and business applications to establish a consistent source of truth • Design, execute, and analyze experiments with retail partners, including price and assortment tests • Partner with engineering to build LLM-assisted analytics tools, including natural-language question-and-answer capabilities over the data warehouse, with evaluation methods, accuracy standards, and guardrails • Support finance and corporate development with analytical modeling for acquisitions, capital projects, facility decisions, and other strategic initiatives • Lead and mentor the Data Scientist • Establish and maintain review standards for analytical code, methodologies, documentation, and business communication • Present analytical findings, models, and recommendations to executive leadership and explain and defend the underlying methodology and assumptions • Collaborate across data, engineering, operations, finance, and commercial teams to translate complex business problems into practical analytical solutions

🎯 Requirements

• 5+ years of experience in data science, operations research, advanced analytics, or a related field • Experience applying forecasting and inventory methods in production environments, including intermittent and hierarchical demand forecasting and service-level-based safety stock • Experience with optimization techniques such as linear programming (LP) or mixed-integer programming (MIP), using OR-Tools, PuLP, Pyomo, or similar platforms, or experience developing practical scheduling heuristics • Expert-level SQL and Python skills • Experience developing production-quality code maintained in Git • Ability to investigate and reconcile conflicting metrics or reports and establish a consistent definition or source of truth across teams • Strong analytical judgment and ability to evaluate assumptions, methodologies, and limitations • Excellent communication skills, including presenting complex analytical concepts to executive leadership and explaining and defending analytical methods • Leadership or mentoring experience • Preferred: experience with injection molding, plastics manufacturing, or multi-plant S&OP • Preferred: experience with Microsoft Fabric and Power BI semantic models • Preferred: experience using LLM APIs, including Anthropic or OpenAI, in production analytics tools or applications • Preferred: experience formally managing or mentoring analysts or data scientists