
Senior Data Scientist & Machine Learning Engineer
NEW YORK, NYJobSeen 1w agoSeen in employer's feed 6 days ago
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Job overview
Chobani is seeking a Senior Data Scientist / Machine Learning Engineer for its Data & Analytics organization. The role focuses on measurement, forecasting, planning, optimization, machine learning, and AI-enabled decision support. It partners with business and data teams to build scalable analytical solutions, initially supporting retail execution use cases and potentially expanding to commercial analytics, planning, operations, and broader advanced analytics initiatives.
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Full job description
SummaryWe are seeking a Senior Data Scientist / Machine Learning Engineer to support Chobani's Data & Analytics organization with a strong focus on measurement, forecasting, planning, optimization, machine learning, and AI-enabled decision support.This role will partner closely with Retail Execution, Commercial, Finance, Supply Chain, Analytics Engineering, Data Engineering and other cross-functional teams to translate business questions into scalable analytical and machine learning solutions. The ideal candidate combines strong data science and machine learning expertise with practical software engineering skills, business partnership, and the ability to build reusable tools that support decision-making across the organization.The initial focus of this role may include retail execution use cases, such as measuring the impact of store-level interventions, forecasting sales and order trends, out of stock modeling, identifying execution risks, and developing models that help prioritize field activity. Over time, this role may support broader One Chobani initiatives across commercial analytics, planning, operations, AI enablement and advanced analytics.ResponsibilitiesData Science, Measurement & Forecasting * Design and develop data science models to support retail execution measurement, forecasting, planning, optimization and decision support across business functions. * Build reusable approaches to measure the incremental impact of store-level activities such as coolers, displays, sampling, field visits, promotions, out-of-stock interventions and other commercial programs. * Develop forecasting models for sales, orders, demand pacing, out-of-stock risk, store-level performance trends and other business planning needs. * Apply statistical modeling, machine learning, causal inference, optimization, supervised learning, time-series forecasting, and other advanced analytical techniques to answer complex business questions. * Create clear diagnostics, assumptions, and confidence measures so model outputs can be understood and trusted by business stakeholders.Machine Learning Engineering & AI Enablement * Build scalable, reusable Python-based tools, libraries, models, and analytical services that can support multiple business use cases. * Partner with Data Engineering and Analytics Engineering teams to integrate models with Snowflake, dbt, POS data, retail execution data, master data, and external data sources. * Support AI-enabled use cases including image analysis, OCR, NLP / LLM workflows, anomaly detection, and recommendation models. * Help convert prototypes and proof-of-concepts into production-grade solutions with appropriate documentation, testing, monitoring, and deployment standards. * Identify opportunities to automate manual analysis and create repeatable decision-support capabilities.Business Partnership & Communication * Partner with Retail Execution and cross-functional business teams to understand priorities, define analytical requirements, and translate business needs into technical solutions. * Communicate complex modeling approaches and trade-offs clearly to both technical and non-technical audiences. * Synthesize model outputs into actionable recommendations, business readouts, dashboards, alerts, or decision-support tools. * Proactively identify high-value data science opportunities that can improve execution, resource allocation, forecasting accuracy, and commercial performance.Data Strategy & Enablement * Contribute to the development of reusable data science frameworks, model standards, and best practices across the Data & Analytics organization. * Collaborate with data teams to improve data quality, store and product linkage, common event definitions, and analytical foundations required for scalable modeling. * Support the broader roadmap for AI, machine learning, and advanced analytics across Chobani.RequirementsThe requirements of this positi
How this job compares
Set against the 4,830 open Data Scientist jobs on Olive Jobs, counted November 3, 2026.
- Pay
- This postingNot listed
- New York median$150–210K/yr363 salary ranges
- US median$58–75/hr136 hourly ranges
- Openings
- Olive Jobs lists 468 open Data Scientist jobs in New York and 4,830 across the US. 6% of them nationwide are listed as remote or flexible.
- Hiring the most in New York
- Capital One47 open
- PwC20 open
- Amazon14 open
- Experience
- Data Scientist postings that state a minimum ask for 5 years of experience at the median; the middle half ask for 3 to 6 years (4,140 postings).
- Education
- 2,278 of the 4,830 open Data Scientist jobs (47%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 3, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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