Staff/Senior Machine Learning Scientist - Pricing/Forecasting in United States at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff/Senior Machine Learning Scientist - Pricing/Forecasting in United States.

This is a high-impact machine learning role focused on building and scaling production-grade forecasting and pricing systems that directly influence business decisions at scale. In this position, you will own end-to-end ML lifecycle development, from model design and feature engineering to deployment, monitoring, and continuous improvement. You will work on either demand forecasting or pricing optimization, applying advanced statistical and probabilistic methods to real-world commercial problems. The role sits within a mature data science environment that emphasizes production reliability, rigorous evaluation, and measurable business outcomes. You will collaborate closely with cross-functional teams including finance, operations, marketing, and engineering to translate business needs into scalable ML solutions. This position is ideal for an experienced practitioner who thrives at the intersection of applied machine learning, systems thinking, and business impact.

• Own and operate end-to-end machine learning systems, including scoping, feature engineering, model development, deployment, monitoring, retraining, and ongoing performance improvements.
• Build and maintain production-grade evaluation frameworks, including backtesting systems, validation pipelines, error analysis, and uncertainty quantification.
• Develop scalable forecasting or pricing models depending on assignment, ensuring alignment with business objectives and operational constraints.
• Define success metrics tied to business outcomes and ensure model outputs are interpretable, reliable, and actionable for stakeholders.
• Design and implement AI-assisted development workflows to automate repetitive tasks while maintaining strict quality and validation standards.
• Write production-quality, testable, and reproducible code supporting robust ML pipelines.
• Partner with cross-functional teams to translate business requirements into prioritized ML roadmaps and measurable deliverables.
• Communicate model assumptions, limitations, and risks clearly to technical and non-technical stakeholders.
• Support model lifecycle management including deployment, versioning, monitoring, and retraining strategies.
• Collaborate with engineering and platform teams to ensure scalable infrastructure for ML systems in production.

Forecasting focus (additional responsibilities):

• Build and improve time-series and demand forecasting models across multiple business segments and horizons.
• Apply hierarchical, segmented, and probabilistic forecasting techniques where appropriate.
• Engineer features and calibration methods to improve accuracy, stability, and interpretability of forecasts.
• Develop clear reporting and versioned forecast outputs with transparent assumptions and uncertainty communication.
• Collaborate with operations, supply chain, finance, and marketing stakeholders to inform planning decisions.

Pricing focus (additional responsibilities):

• Lead the design and maintenance of automated pricing systems, including Bayesian hierarchical modeling and inference pipelines.
• Design and analyze A/B tests and backtests to evaluate pricing strategies and revenue impact.
• Optimize pricing systems while balancing revenue goals, brand considerations, and market stability.
• Evaluate and evolve system architecture, making recommendations for improvements or migrations.
• Collaborate with adjacent pricing teams to align methodologies and share infrastructure where applicable.

Requirements:

• 5+ years of applied machine learning or data science experience with production model ownership.
• Strong experience in forecasting OR Bayesian/probabilistic modeling and statistical inference.
• Proven track record building and maintaining end-to-end ML systems in production environments.
• Deep understanding of time-series modeling, backtesting, and model evaluation techniques.
• Strong programming skills in Python (or R) and SQL, with production-quality coding practices.
• Solid foundation in statistics, including probabilistic reasoning and uncertainty quantification.
• Experience designing and deploying monitoring, retraining, and validation pipelines.
• Ability to communicate complex analytical concepts clearly to non-technical stakeholders.
• Experience collaborating across business, engineering, and product teams in cross-functional environments.
• Familiarity with AI-assisted development workflows and emphasis on reproducibility and quality control.

Staff-level expectations (preferred):

• 8+ years of applied ML experience or PhD with 3+ years industry experience.
• Proven ability to lead ML system architecture decisions and improve existing production systems.
• Experience mentoring and providing technical leadership to other data scientists or ML engineers.
• Strong ownership mindset with ability to independently manage complex, multi-component systems.

Benefits:

• Competitive salary range of $180,000 – $250,000 USD depending on level and experience.
• Annual bonus or profit participation program based on company performance.
• Comprehensive health coverage including medical, dental, vision, and prescription plans.
• Retirement savings plans including 401(k) with pre-tax and Roth options.
• Generous paid time off and flexible leave policies.
• Disability, life, and additional insurance coverage options.
• Remote-friendly work structure (U.S.-based).
• Professional development and educational assistance programs.
• Exposure to large-scale, production-critical ML systems in forecasting and pricing.
• Collaborative, innovation-driven environment focused on measurable impact.