Jobs · OTHR · New York

Senior Data Scientist

TechWish · New York, NY · 1 mo ago
On-siteOTHRFull-time

About the Role

This is a 3-month contract position located in Mexico, with the possibility of extension. Bill rates will be determined as per the Master Service Agreement (MSA) and may offer limited flexibility.

Requirements

  • 5-8 years of hands-on experience in data science, with a strong track record of delivering production-grade solutions in business environments.
  • Deep expertise in traditional machine learning techniques, including time series forecasting (e.g., ARIMA, SARIMA), regression models, and other statistical methods applied to real-world datasets.
  • Proven experience designing and implementing optimization models (e.g., linear programming, mixed-integer programming, heuristics) to solve complex business problems such as demand planning, inventory optimization, or resource allocation.
  • Recent, demonstrable experience working on Generative AI initiatives, including LLM-based solutions and agentic workflows (e.g., autonomous agents, multi-step reasoning pipelines, tool-augmented AI systems).
  • Hands-on experience in designing, deploying, and operationalizing agentic workflows in production environments, including orchestration, tool integration, monitoring, and performance optimization of AI-driven agents.
  • Strong domain knowledge in Consumer-Packaged Goods (CPG), with hands-on experience in at least one functional area: Sales (e.g., demand forecasting, pricing), Finance (e.g., revenue/margin analytics), or Supply Chain (e.g., planning, logistics, inventory).
  • Ability to translate business problems into scalable analytical and AI-driven solutions, partnering closely with cross-functional stakeholders such as product managers, engineers, and business teams.
  • 100% hands-on role with active involvement in data exploration, model development, evaluation, deployment, and continuous improvement.
  • Proficiency in Python and relevant data science ecosystems (e.g., pandas, scikit-learn, statsmodels, PyTorch/TensorFlow), along with experience in cloud platforms and MLOps practices.

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