Senior Data Scientist

Global Sports Jobs Limited; Pahokee (FL); Presencial; USD 120 000 - 180 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Generous total rewards package

Casual work environment

Diverse and inclusive culture

Electric atmosphere for professional开发

Resumo da oferta

Nike is seeking a Data Scientist within the Data Science & Advanced Analytics team, part of SCPT, contributing to manufacturing, materials sourcing, and supply planning. You will design predictive and prescriptive analytical solutions, build end-to-end pipelines, and collaborate with data engineers, product owners, and business end users to deliver scalable insights for global supply chain decisions.

The role emphasizes advanced modelling, productionisation, and cross-functional leadership to

Qualificações

• Advanced quantitative degree in Statistics, Mathematics, Operations Research, Computer Science or a related field and at least 5 years of related industry experience as a data scientist or applied scientist, or a Bachelor's degree and 7-12 years of related work experience.
• Dependable teammate with drive, curiosity, strong hands-on data science and analytics experience including forecasting, optimisation, and simulation, and a deep understanding of supply chain and operations.
• Ability to rise above the numbers and explain complex insights to users at all levels, and to simplify and distil business complexity into testable hypotheses and scalable solutions.
• Proficiency in various advanced modelling techniques, with the ability to identify the optimal technique based on business requirements, available data, and the technique's assumptions, interpretability, robustness, and limitations.
• Consulting mindset; asks good questions, continually learns and keeps up with state-of-the-art developments, and finds opportunities to share knowledge with others.
• Deep knowledge and experience in supply chain, supply planning, manufacturing and sourcing, and logistics.
• Hands-on ability and knowledge in data engineering, software engineering, and at-scale production.
• Proven track record of working cross-functionally and having a consulting mindset to critically evaluate complex business information from multiple perspectives, including questioning assumptions and validity.
• Familiarity with the Agile development process and ability to prepare a project plan, communicate it to the team, and break work into trackable tasks.

Responsabilidades

• Design, develop, and productionise optimisation and analytical models to support supply chain decisions, applying statistical modelling and simulation techniques and conducting model performance, scenario, and sensitivity analysis.
• Build and maintain end-to-end analytical pipelines covering data ingestion, feature engineering, model training, validation, and deployment.
• Work with the squad and global supply chain and operations partners to assess business requirements, data constraints, and trade-offs of alternative modelling techniques, contributing to planning, scheduling, and value measurement to meet timeline targets and success criteria.
• Explore business drivers of cost, on-time performance of products and materials, and root causes of quality issues, while striving to achieve Nike's sustainability goals.
• Help shape Nike's analytical platforms and products by identifying foundational data science capabilities and creating reusable analytical components.
• Support the adoption of analytical products through effective storytelling and collaboration with key partners.
• Share knowledge with the wider team and contribute to best practices for model governance, reproducibility, and responsible use of data science solutions.
• Influence product direction, guide standard methodologies in data science and engineering, and help deliver technical projects from inception to completion.

Descrição da oferta de emprego

About the Role

This role sits within Nike's Data Science & Advanced Analytics team, which is part of Supply Chain and Planning Technology (SCPT) and works in the Sourcing, Supply, and Manufacturing (SSM) squad. The role is part of a cross-functional Agile squad and provides technical expertise and leadership in building predictive and prescriptive analytical solutions for Nike's global supply chain and operations, specifically in manufacturing, materials sourcing, and supply planning. The role reports to the Director of Data Science and collaborates with data science leads, data and software engineers, product owners and managers, and business end users to deliver analytical and optimisation solutions.

Key Responsibilities

• Design, develop, and productionise optimisation and analytical models to support supply chain decisions, applying statistical modelling and simulation techniques and conducting model performance, scenario, and sensitivity analysis.
• Build and maintain end-to-end analytical pipelines covering data ingestion, feature engineering, model training, validation, and deployment.
• Work with the squad and global supply chain and operations partners to assess business requirements, data constraints, and trade-offs of alternative modelling techniques, contributing to planning, scheduling, and value measurement to meet timeline targets and success criteria.
• Explore business drivers of cost, on-time performance of products and materials, and root causes of quality issues, while striving to achieve Nike's sustainability goals.
• Help shape Nike's analytical platforms and products by identifying foundational data science capabilities and creating reusable analytical components.
• Support the adoption of analytical products through effective storytelling and collaboration with key partners.
• Share knowledge with the wider team and contribute to best practices for model governance, reproducibility, and responsible use of data science solutions.
• Influence product direction, guide standard methodologies in data science and engineering, and help deliver technical projects from inception to completion.

Required Experience & Qualifications

• Advanced quantitative degree in Statistics, Mathematics, Operations Research, Computer Science or a related field and at least 5 years of related industry experience as a data scientist or applied scientist, or a Bachelor's degree and 7-12 years of related work experience
• Any suitable combination of education, experience or training is accepted.
• Dependable teammate with drive, curiosity, strong hands-on data science and analytics experience including forecasting, optimisation, and simulation, and a deep understanding of supply chain and operations.
• Ability to rise above the numbers and explain complex insights to users at all levels, and to simplify and distil business complexity into testable hypotheses and scalable solutions.
• Proficiency in various advanced modelling techniques, with the ability to identify the optimal technique based on business requirements, available data, and the technique's assumptions, interpretability, robustness, and limitations.
• Consulting mindset; asks good questions, continually learns and keeps up with state-of-the-art developments, and finds opportunities to share knowledge with others.
• Deep knowledge of and hands-on ability in data science and optimisation methodologies, including classical models, artificial intelligence and machine learning algorithms, and linear and non-linear optimisation techniques
• Hands-on experience building optimisation models using Python and commercial solvers such as Gurobi, CPLEX, or equivalent.
• Advanced skills in programming languages, particularly Python and SQL, applied to data acquisition, preprocessing, modelling, and monitoring.
• Familiarity with a wide range of data science and analytics software tools, including Jupyter Notebook, SQL consoles, Hadoop, and Spark, and with cloud computing platforms such as AWS and Databricks.
• Experience building, training, scoring, tuning, and maintaining predictive models in production at enterprise scale, and familiarity with mainstream packages relevant to managing all stages of the model lifecycle.
• Deep knowledge and experience in supply chain, supply planning, manufacturing and sourcing, and logistics.
• Hands-on ability and knowledge in data engineering, software engineering, and at-scale production.
• Proven track record of working cross-functionally and having a consulting mindset to critically evaluate complex business information from multiple perspectives, including questioning assumptions and validity.
• Familiarity with the Agile development process and ability to prepare a project plan, communicate it to the team, and break work into trackable tasks.

Benefits & Perks

• Generous total rewards package.
• Casual work environment.
• Diverse and inclusive culture.
• Electric atmosphere for professional development.

The Application Process

Accommodations are available to complete the interview process, including screen readers, sign language interpreters, accessible and single-location in-person interviews, closed captioning, and other reasonable modifications as needed.