Senior Data Scientist – Data Quality
Employment Information
Job Description
Data Scientist responsible for managing data pipelines and deploying AI models for trade intelligence. Collaborating with teams to enhance the decision-making process in commercial strategies.
Responsibilities:
- Own the Data: Command the full lifecycle of data pipelines — ingestion, cleaning, structuring, and analysis of large-scale, noisy, analog signals.
- Operationalize AI: Design, train, and deploy ML/AI models (including LLMs, predictive systems, and demand-forecasting models) into production environments.
- Execution at Velocity: Move from prototype to deployment with speed, reliability, and measurable accuracy.
- Model for Impact: Build systems that optimize quality control performance and decrease latency or deliver intelligence that drives customer growth with operational leverage.
- Domain Partnership: Work directly with Engineering, Product, and Commercial teams to ensure models translate into measurable outcomes, not academic outputs.
- Evolve the Platform: Advance the intelligence layer that makes the world’s largest commercial channel legible and actionable. Performance is assessed on one axis: the velocity, precision, and scale at which data science converts fragmented analog signals into decisive market intelligence.
Requirements:
- Raw talent: Demonstrated success in building and deploying AI/ML systems that operate in production at scale.
- Technical Mastery: Deep fluency in Python or R or SQL, distributed data systems, and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, sktime, vetiver, tidymodels).
- Machine Learning Experience: Hands-on experience with predictive modeling, time series and forecasting algorithms, data pipelines and model validations and fine-tuning. LLM integration for real-time inference appreciated.
- Operational Rigor: Ability to deliver reliable systems under constraints—limited resources, ambiguous inputs, and high-pressure timelines.
- Commercial Awareness: Familiarity with how CPG manufacturers and distributors execute in the market, and how data translates into demand planning, distribution, and retail execution.
- Velocity and Precision: Bias toward decisive action, measured by speed of deployment and model accuracy in the field.
- Explorer Mindset. Masterfully handles intricate datasets to find opportunities. And expert on detailed Exploratory Data Analysis and descriptive techniques to understand market behavior and unexplored patterns.
- Experience with data visualization frameworks appreciated (e.g. Matplotlib, Seaborn, Ggplot2, Echarts, etc.)
- Scalable Value Delivery: Build models that drive repeatable outcomes, not bespoke analysis.
Benefits:
- No Credentialism: Degrees, pedigrees, and credentials are irrelevant. What matters is capability; decisive executors who operationalize AI and deliver intelligence-grade results.
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