Must have 14+ yrs of Exp. || Lead Data Scientist (Demand Forecasting - Supply Chain) (14+ yrs) || Bristlecone || Bay Area, CA (Hybrid) || Contact

[Deepak Singh]

Greetings,

Hope you are doing well!

We are looking for a Lead Data Scientist. Below is the job description for your reference. Please have a look and share the best level of your interest.

Role: Lead Data Scientist (Demand Forecasting - Supply Chain) (14+ yrs)

Client: Bristlecone

Location: Bay Area, CA (Hybrid)

Type: Contract 

Job Description:

We are hiring a Lead Data Scientist to be the primary technical engine of our supply chain demand forecasting and root cause analysis platform. This is a hands-on senior individual contributor role with significant ownership — you will implement, validate, and maintain the full ML pipeline, working closely with the US-based Senior Manager.

Required Qualifications

Experience

• 9–12 years of hands-on experience in data science or machine learning — with a strong emphasis on Python-based ML engineering in production environments
• 3+ years of experience with time-series forecasting or supply chain analytics in a commercial context
• Demonstrated experience building end-to-end ML pipelines from raw tabular data through model output and reporting — not just notebook prototyping
• Experience working in cross-functional teams with stakeholders across business, IT, and analytics; ideally in a consulting or professional services environment
• Track record of delivering high-quality, well-documented, reviewable code in a team setting

Technical Skills

• Expert-level Python: scikit-learn, pandas, numpy, scipy, joblib — able to write production-grade, optimised code for large datasets
• Deep hands-on experience with ensemble methods: gradient boosting (GBM, XGBoost, LightGBM) and Random Forest — including hyperparameter tuning and performance diagnostics
• Proficiency in quantile regression and probabilistic forecasting: building tree-level percentile prediction intervals, measuring PI coverage (Winkler score, pinball loss), and detecting quantile crossing violations
• Strong statistical skills: KS 2-sample tests, ACF/PACF analysis, change-point detection, IQR outlier detection, Pearson/Spearman correlation
• Proficiency with SQL for data extraction, transformation, and validation
• Familiarity with version control (Git), experiment reproducibility (SEED management, config-driven pipelines), and collaborative development workflows

Education

• Master's degree or PhD in Data Science, Statistics, Computer Science, Machine Learning, Operations Research, or a related quantitative field
• Bachelor's degree with equivalent industry experience in a quantitative discipline considered

Preferred Qualifications

• Experience with intermittent demand modelling: Croston method, SBA, ADI and CV² classification for routing parts to appropriate forecast models
• Experience with reconciliation frameworks: bottom-up and top-down forecast reconciliation, MinT reconciliation, hierarchical coherence
• Familiarity with MLflow, DVC, or equivalent tools for experiment tracking and pipeline orchestration
• Experience with cloud platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) for scalable model training and deployment
• Knowledge of S&OP processes, IBP (Integrated Business Planning), and multi-echelon inventory theory
• Experience building user-facing analytical tools or dashboards — ideally with some exposure to full-stack data product development
• Contributions to open-source ML projects or published work in forecasting, supply chain analytics, or applied ML

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Regards,

Deepak Singh

Technical Team Lead

Email: Dsr.itr...@gmail.com

LinkedIn: www.linkedin.com/in/deepak-singh-rajput-8a7b6a21a/

221 River St 9^th floor Hoboken, NJ 07030