Open to remote work except in South Dakota, Vermont and West Virginia. The annual base salary for this position ranges from $119,400.00 in our lowest geographic market to $267,500.00 in our highest geographic market. Actual salary will vary based on a candidate's location, qualifications, skills and experience. Information about benefits can be found here. Become a Part of the NIKE, Inc. Team NIKE, Inc. is a place to explore potential, push boundaries and push out the edges of what can be. The company looks for people who can grow, think, dream, and build. Its culture thrives by embracing diversity and exciting inventiveness. At NIKE, Inc. it's about each person bringing skills and passion to an exciting and constantly evolving game! Who we are looking for Working at Nike in this time of growth and dynamic strategic intent is a unique opportunity; we are looking for a professional who is passionate about the Nike brand, energetic and proactive, and thrives on working at the intersection of data and business. We're looking for a Lead Data Scientist to join Nike's Global Consumer Data Science organization, supporting the measurement of our Consumer Marketing channels to optimize Nike's marketing strategy. This is a new position in the Marketing Data Science team, which will focus on evolving Nike's Marketing Mix Modeling (MMM) capability, playing a meaningful role in shaping how marketing effectiveness is measured. We seek an individual with hands-on experience in MMM. This person will be comfortable getting their hands dirty with exploratory data analysis, coding, and modeling. They will also collaborate with team-members and partners, assuring that we are crafting the best solutions for evolving business needs. A successful candidate has a comprehensive grasp of the MMM development process, and experience leveraging standard data science tools (PySpark, Pandas, Scikit, XGBoost, etc.), platforms (i.e. Databricks, Sagemaker, Python) and cloud providers (AWS/MS Azure). As a lead data scientist in the team, you will be responsible for designing and developing innovative measurement and marketing mix models, while coordinating with fellow data scientists, marketers and machine learning engineers to solve key challenges facing the teams. What you will work on This person will join a team that is responsible for measurement and optimization of Marketing Effectiveness on behalf of the Marketing organization. You will work closely with Data Science and Marketing Science teammates to build, support, and enable Marketing/Media Mix Modeling (MMM) and related forecasting & budgeting use cases. Build credibility for MMM approaches through demonstrating functional expertise and experience. Simultaneously innovating to drive more granular and frequent measurement, and broader adoption across the organization. Establish and support large-scale measurement and optimization of MMM for different geographies in a production/testing environment. Improve and consult on MMM to connect the impact of marketing drivers and business short-term and long-term outcomes. Partner with peers in both Data Science and Marketing Science, developing scalable data, improving current MMM models, and modeling processes. Use common tools and instruments to help establish operational excellence for MMM. Drive the application and implementation of innovative best-in-class methods and tools to derive useful insights for a wide variety of business goals in support of marketing efforts. Stay up to date on industry trends, tools, and platform capabilities relevant to the team's disciplines. Who you will work with Reporting to the Director of Marketing Data Science, you will work with internal teams across Global Insights, Data Science & Analytics as well as external media agencies and platform partners, to build and deploy consistent and scalable measurement solutions. What you bring <ul><li>Bachelor's degree in Mathematics, Statistics, Machine Learning, Data Science, or related quantitative field preferred</li><li>4-7 years of hands-on experience, industry experience in the development of marketing mix models, real-time forecasting, and optimization media tools</li><li>Advanced programming skills using Python and SQL</li><li>Hands-on experience with standards data science & analytics tools like PySpark, Pandas, Scikit, XGBoost, etc.</li><li>Experience with cloud based platforms and providers (i.e., AWS, Databricks, Sagemaker, Microsoft Azure).</li><li>Hands-on experience with marketing mix platforms, such as the following: PyMC, Google's LightweightMMM, Google's Meridian or Facebook's Robyn.</li><li>Hands-on experience with advanced statistical and/or machine learning methodologies, such as the following: Bayesian regression, gradient boosting regression, general linear models, other type of regressions (i.e. ridge/lasso, random, etc), time-series models, media optimization engine simulators, etc.</li><li>Proven experience cleansing, manipulating, and transforming multiple input data sources (i.e. media, macro, merchandise/operation data, etc)</li><li>Established experience implementing MMM to impact marketing channel strategy</li><li>Strong analytical skills and proven capability to apply data to business & marketing decisions</li></ul>

Open to remote work except in South Dakota, Vermont and West Virginia. The annual base salary for this position ranges from $119,400.00 in our lowest geographic market to $267,500.00 in our highest geographic market. Actual salary will vary based on a candidate's location, qualifications, skills and experience. Information about benefits can be found here (. Become a Part of the NIKE, Inc. Team NIKE, Inc. is a place to explore potential, push boundaries and push out the edges of what can be. The company looks for people who can grow, think, dream, and build. Its culture thrives by embracing diversity and exciting inventiveness. At NIKE, Inc. it's about each person bringing skills and passion to an exciting and constantly evolving game! Who we are looking for Working at Nike in this time of growth and dynamic strategic intent is a unique opportunity; we are looking for a professional who is passionate about the Nike brand, energetic and proactive, and thrives on working at the intersection of data and business. We're looking for a Lead Data Scientist to join Nike's Global Consumer Data Science organization, supporting the measurement of our Consumer Marketing channels to optimize Nike's marketing strategy. This is a new position in the Marketing Data Science team, which will focus on evolving Nike's Marketing Mix Modeling (MMM) capability, playing a meaningful role in shaping how marketing effectiveness is measured. We seek an individual with hands-on experience in MMM. This person will be comfortable getting their hands dirty with exploratory data analysis, coding, and modeling. They will also collaborate with team-members and partners, assuring that we are crafting the best solutions for evolving business needs. A successful candidate has a comprehensive grasp of the MMM development process, and experience leveraging standard data science tools (PySpark, Pandas, Scikit, XGBoost, etc.), platforms (i.e. Databricks, Sagemaker, Python) and cloud providers (AWS/MS Azure). As a lead data scientist in the team, you will be responsible for designing and developing innovative measurement and marketing mix models, while coordinating with fellow data scientists, marketers and machine learning engineers to solve key challenges facing the teams. What you will work on This person will join a team that is responsible for measurement and optimization of Marketing Effectiveness on behalf of the Marketing organization. You will work closely with Data Science and Marketing Science teammates to build, support, and enable Marketing/Media Mix Modeling (MMM) and related forecasting & budgeting use cases. Build credibility for MMM approaches through demonstrating functional expertise and experience. Simultaneously innovating to drive more granular and frequent measurement, and broader adoption across the organization. Establish and support large-scale measurement and optimization of MMM for different geographies in a production/testing environment. Improve and consult on MMM to connect the impact of marketing drivers and business short-term and long-term outcomes. Partner with peers in both Data Science and Marketing Science, developing scalable data, improving current MMM models, and modeling processes. Use common tools and instruments to help establish operational excellence for MMM. Drive the application and implementation of innovative best-in-class methods and tools to derive useful insights for a wide variety of business goals in support of marketing efforts. Stay up to date on industry trends, tools, and platform capabilities relevant to the team's disciplines. Who you will work with Reporting to the Director of Marketing Data Science, you will work with internal teams across Global Insights, Data Science & Analytics as well as external media agencies and platform partners, to build and deploy consistent and scalable measurement solutions. What you bring Bachelor's degree in Mathematics, Statistics, Machine Learning, Data Science, or related quantitative field preferred 4-7 years of hands-on experience, industry experience in the development of marketing mix models, real-time forecasting, and optimization media tools Advanced programming skills using Python and SQL Hands-on experience with standards data science & analytics tools like PySpark, Pandas, Scikit, XGBoost, etc. Experience with cloud based platforms and providers (i.e., AWS, Databricks, Sagemaker, Microsoft Azure). Hands-on experience with marketing mix platforms, such as the following: PyMC, Google's LightweightMMM, Google's Meridian or Facebook's Robyn. Hands-on experience with advanced statistical and/or machine learning methodologies, such as the following: Bayesian regression, gradient boosting regression, general linear models, other type of regressions (i.e. ridge/lasso, random, etc), time-series models, media optimization engine simulators, etc. Proven experience cleansing, manipulating, and transforming multiple input data sources (i.e. media, macro, merchandise/operation data, etc) Established experience implementing MMM to impact marketing channel strategy Strong analytical skills and proven capability to apply data to business & marketing decisions NIKE, Inc. is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, protected veteran status, or disability. NIKE is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the employment process, please call +1 503-671-4156 and let us know the nature of your request, your location and your contact information.

We have an immediate opportunity for a data scientist specializing in machine learning to join our dynamic and growing technology team. This role involves developing and implementing machine learning algorithms, primarily for food classification via machine vision, managing large datasets, optimizing machine vision models, and driving innovation for AI-based food waste prevention solutions. The role is part of our machine vision team and will report to our VP of Product.

Zostań członkiem zespołu NIKE, Inc. NIKE, Inc. to nie tylko firma, która ubiera najlepszych sportowców na świecie. To miejsce, w którym możesz odkryć swój potencjał, przekroczyć granice oraz sprawić, że niemożliwe staje się możliwe. Firma poszukuje ludzi, którzy chcą się rozwijać i potrafią myśleć, marzyć oraz tworzyć. Jej kultura rozwija się dzięki różnorodności i wspieraniu kreatywności. Potrzebni są w niej ludzie ambitni, urodzeni liderzy i prawdziwi wizjonerzy. W NIKE, Inc. każda osoba wnosi do gry swoje umiejętności oraz pasje. Dzięki temu ciągle się rozwijamy. Open to remote work except in South Dakota, Vermont and West Virginia.
The annual base salary for this position ranges from $99,500.00 in our lowest geographic market to $222,900.00 in our highest geographic market. Actual salary will vary based on a candidate's location, qualifications, skills and experience. Information about benefits can be found here . Analytics is a competitive differentiator for Nike and is fundamentally changing how the company serves athletes and consumers around the world! Our Nike Insights Data Science and Analytics team builds analytic-based solutions to manage marketplace and optimize the supply chain. Using big data, advanced analytics and innovative technology, the team strives to ensure that Nike gets the right product to the right place at the right time for the consumers
Who we are looking for
We are looking for a Sr Data Scientist to join our Merch Financial Planning Data Science team within Insights Data Science and Analytics focused overall Nike's growth over next several years. This role will be part of a multi-functional agile squad responsible for using predictive analytics to forecast consumer demand, enhance decision making and drive to action against our strategic priorities. Does this sound like you?
The candidate needs to be a dependable teammate with strong hands-on analytics experience, drive, and curiosity. You know how to rise above the numbers and explain the crucial insights to users at all levels. You simplify and distill business complexity into testable hypotheses and scalable solutions. While you are well versed in a plethora of sophisticated modeling techniques, you can identify the technique optimal for the task at hand based on the business requirements, your knowledge of the data and the technique’s assumptions, interpretability and robustness. You ask good questions, are continually learning as well as finding opportunities to share knowledge with others!
What you will work on
If this is you, you will be part of an Enterprise Data Science, Merch Financial Planning squad. We deliver scalable solutions to power data driven automated decision making on a variety of planning problems and other related key business decisions. Specifically, you will:
Develop new sophisticated algorithms and improve existing approaches based on statistical/econometric methods, machine learning techniques and big data solutions to forecast consumer demand and determine optimal level of investment in various stages of the supply chain. Identify and apply methods to acquire, explore, cleanse, and fuse data from different sources. Design, write, own and maintain production grade analytics code to support forecasting models. Review and ensure code quality of peers. Assess business requirements and constraints to make trade-off recommendations between speed and accuracy of alternative solution approaches. Be a key contributor to building, scoring, deploying, monitoring, updating and promoting Nike’s forecasting platform. Facilitate the planning, scheduling and value measurement of the work to meet timeline targets and success criteria. Support the adoption of analytic products through effective storytelling and collaboration with key partners. Participate in a continuous learning environment within the analytics community through persistent development of new skills and sharing of knowledge through mentorships and contributions to the open-source community. Who you will work with
You will work with the Director of Data Science while partnering daily with fellow data scientists, data analysts, engineers and product owner on your squad. You will collaborate across the broader organization with business teams in Demand and Supply Management as well as other data, analytics and technology functions at Nike.
What you bring
Advanced quantitative degree (Statistics, Mathematics, Economics, Computer Science or related field) and at least 3 years of related industry experience or Bachelor’s degree and 5 years relevant industry experience. Demonstrated expertise with data science methods, machine learning algorithms and production level programming principles. Solid understanding of forecasting techniques, such as surveys, trend analysis, econometric models and machine learning algorithms. Advanced skills in programming languages (particularly Python, Pandas and SQL) and ability to apply them to develop, build and maintain production grade analytics products. Knowledge and experience with demand forecast models and algorithms highly desired. Experience solving retail business problems is a plus. Demonstrated ability to apply programming skills to data acquisition, preprocessing, modeling and monitoring as well as familiarity with the wide range of data science/analytics software tools. Experience with common data science/analytics software tools (e.g. Jupyter Notebook, SQL, Spark, Git) and cloud computing platforms (e.g. Amazon Web Services). Solid understanding of python and spark framework to leverage power of the distributed computing. Experience in building, training, scoring, tuning and maintaining predictive models in production at enterprise scale and familiarity with mainstream packages relevant to managing all stages of Data Science/Analytics lifecycle. Exposure to the Monthly business planning process in Retail and Supply chain would be an advantage. NIKE, Inc. to firma skupiona na rozwoju, której zależy również na rozwoju pracowników. Nike oferuje bogaty pakiet dodatków oraz luźną i energiczną atmosferę w pracy, by wspierać rozwój zawodowy pracowników. Koncentruje się także na wzmacnianiu inkluzywnej kultury promującej integrację. Niezależnie od lokalizacji czy stanowiska, każdy pracownik Nike dąży do realizacji jednej niesłychanie istotnej misji. Jest nią wnoszenie inspiracji i innowacji w życie każdego sportowca* na świecie.
NIKE, Inc. zależy na zatrudnianiu zróżnicowanych osób. Kandydatura osób, które się zakwalifikują, będzie brana pod uwagę bez względu na rasę, kolor skóry, wyznanie, płeć, pochodzenie, wiek, orientację seksualną, tożsamość płciową, wyrażanie płciowości, status weterana czy niepełnosprawność. #J-18808-Ljbffr

Open to remote work except in South Dakota, Vermont and West Virginia. The annual base salary for this position ranges from $99,500.00 in our lowest geographic market to $222,900.00 in our highest geographic market. Actual salary will vary based on a candidate's location, qualifications, skills and experience. Information about benefits can be found here. Analytics is a competitive differentiator for Nike and is fundamentally changing how the company serves athletes and consumers around the world! Our Nike Insights Data Science and Analytics team builds analytic-based solutions to manage marketplace and optimize the supply chain. Using big data, advanced analytics and innovative technology, the team strives to ensure that Nike gets the right product to the right place at the right time for the consumers Who we are looking for We are looking for a Sr Data Scientist to join our Merch Financial Planning Data Science team within Insights Data Science and Analytics focused overall Nike's growth over next several years. This role will be part of a multi-functional agile squad responsible for using predictive analytics to forecast consumer demand, enhance decision making and drive to action against our strategic priorities. Does this sound like you? The candidate needs to be a dependable teammate with strong hands-on analytics experience, drive, and curiosity. You know how to rise above the numbers and explain the crucial insights to users at all levels. You simplify and distill business complexity into testable hypotheses and scalable solutions. While you are well versed in a plethora of sophisticated modeling techniques, you can identify the technique optimal for the task at hand based on the business requirements, your knowledge of the data and the technique's assumptions, interpretability and robustness. You ask good questions, are continually learning as well as finding opportunities to share knowledge with others! What you will work on If this is you, you will be part of an Enterprise Data Science, Merch Financial Planning squad. We deliver scalable solutions to power data driven automated decision making on a variety of planning problems and other related key business decisions. Specifically, you will: <ul><li>Develop new sophisticated algorithms and improve existing approaches based on statistical/econometric methods, machine learning techniques and big data solutions to forecast consumer demand and determine optimal level of investment in various stages of the supply chain.</li><li>Identify and apply methods to acquire, explore, cleanse, and fuse data from different sources.</li><li>Design, write, own and maintain production grade analytics code to support forecasting models. Review and ensure code quality of peers.</li><li>Assess business requirements and constraints to make trade-off recommendations between speed and accuracy of alternative solution approaches.</li><li>Be a key contributor to building, scoring, deploying, monitoring, updating and promoting Nike's forecasting platform.</li><li>Facilitate the planning, scheduling and value measurement of the work to meet timeline targets and success criteria.</li><li>Support the adoption of analytic products through effective storytelling and collaboration with key partners.</li><li>Participate in a continuous learning environment within the analytics community through persistent development of new skills and sharing of knowledge through mentorships and contributions to the open-source community.</li></ul> Who you will work with You will work with the Director of Data Science while partnering daily with fellow data scientists, data analysts, engineers and product owner on your squad. You will collaborate across the broader organization with business teams in Demand and Supply Management as well as other data, analytics and technology functions at Nike. What you bring <ul><li>Advanced quantitative degree (Statistics, Mathematics, Economics, Computer Science or related field) and at least 3 years of related industry experience or Bachelor's degree and 5 years relevant industry experience.</li><li>Demonstrated expertise with data science methods, machine learning algorithms and production level programming principles.</li><li>Solid understanding of forecasting techniques, such as surveys, trend analysis, econometric models and machine learning algorithms.</li><li>Advanced skills in programming languages (particularly Python, Pandas and SQL) and ability to apply them to develop, build and maintain production grade analytics products.</li><li>Knowledge and experience with demand forecast models and algorithms highly desired. Experience solving retail business problems is a plus.</li><li>Demonstrated ability to apply programming skills to data acquisition, preprocessing, modeling and monitoring as well as familiarity with the wide range of data science/analytics software tools.</li><li>Experience with common data science/analytics software tools (e.g. Jupyter Notebook, SQL, Spark, Git) and cloud computing platforms (e.g. Amazon Web Services).</li><li>Solid understanding of python and spark framework to leverage power of the distributed computing.</li><li>Experience in building, training, scoring, tuning and maintaining predictive models in production at enterprise scale and familiarity with mainstream packages relevant to managing all stages of Data Science/Analytics lifecycle.</li><li>Exposure to the Monthly business planning process in Retail and Supply chain would be an advantage.</li></ul>

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Data Scientist Jobs in Beaverton, OR

Lead Data Scientist Remote Work OptionJuly 24, 2024

Lead Data Scientist Remote Work OptionJuly 23, 2024

Lead Data Scientist Remote Work OptionJuly 20, 2024

Lead Data Scientist Remote Work OptionJuly 18, 2024

Machine Learning Data ScientistJuly 10, 2024

Senior Data Scientist Remote Work EligibleJuly 5, 2024

Senior Data Scientist Remote Work EligibleJuly 1, 2024

Senior Data Scientist Remote Work EligibleJune 30, 2024