Principal Data Scientist- E2E
Position SummaryWhat you'll do What you'll doThe Principal Data Scientist on the Walmart Retail Intelligence Team will drive AI discovery, research, algorithmic solution design, and rapid prototyping targeted to deliver important activations within Walmart US.
This role will be focused on operational and execution decision engines with alignment to unified associate signals and workload optimization supported by Retail Science Associate team.
They will be responsible for high level ML/AI conceptualization, feature engineering, ML/AI model development and experimentation, and pilot testing and iterative model refinement.
They will work collaboratively with Product and Tech teams to productionize and scale ML/AI solutions and establish model monitoring and management processes.
This role will require partnership with other teams within the Walmart E2E Fulfillment organization (data governance, science management, retail analytics, customer engine, foundation).
The Principal Data Scientist will play a pivotal in deciding how do we develop ML/AI algorithms, at scale, that are linked to strategic business choices, unified associate signals, efficiency of associate operations, and delivering the desired associate, customer, and/or financial impact.
They own the vision on improving efficiency of data science work streams including prototype development cycle time, model accuracy, model reliability, model stability, coverage of use cases, decisions impact and resources cost savings.
What you'll do:
Apply broad knowledge of ML/AI capabilities to identify growth areas, new and emerging opportunities.
Conducts research by studying organization goals, strategies, practices, and user projects.
Recommends strategies by evaluating organization outcomes; identifying problems; evaluating trends; anticipating requirements.
Influence a team of Data Scientists focused on powering AI/ML solutions within the scope of associate work prioritization, workforce planning and retention strategies.
Partner closely with Data Science Management, Business Leaders, and ML engineering leaders to inform, drive and accelerate innovations in discovery experiences via Insights, frameworks, causal inference solutions and machine learning prototypes.
Execute full life cycle of projects through project planning, data collection, model prototyping and deployment, with responsibilities encompassing stakeholder management and communication to cross-functional partners.
Adhere to MLOps framework to create, build, and deploy data science algorithms continuously test and monitor drifts.
Shares highly complex information related to areas of expertise.
Interacts with senior management to keep abreast of objectives.
Interacts with peers to interpret information and improve cross-functional processes and programs.
Builds and enhances key internal and external contacts.
What you'll bring:
Experience in the development of large-scale ML/AI solutions, Causal Inference and Ranking/Prioritization systems.
6 years
of experience in Applied ML familiar with core supervised and unsupervised algorithms.
Skilled in Programming language (Python) and Large-scale training using data structures and algorithms.
2 years
experience with Causal Inference frameworks, Bayesian Networks and Operations Research methods (Newsvendor problem, Travelling Salesman problem, Shortest Path models, etc.
) Experience with cloud environments including Azure, Google Cloud, etc.
Solid MLOps practices including good design documentation, unit testing, integration testing and source code control (git).
Experienced with agile methodologies using project planning and tracking management tools e.
g.
, JIRA.
Minimum
Qualifications:
Option 1:
Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field.
Option 2:
Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in analytics related field.
Option 3:
8 years' experience in an analytics or related field Preferred
Qualifications:
PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, using open source frameworks (for example, scikit learn, TensorFlow, torch) with 6 years
of experience post graduate degree.
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch) Minimum Qualifications Outlined below are the required minimum qualifications for this position.
If none are listed, there are no minimum qualifications.
Option 1:
Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field.
Option 2:
Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field.
Option 3:
7 years' experience in an analytics or related field Preferred Qualifications Outlined below are the optional preferred qualifications for this position.
If none are listed, there are no preferred qualifications.
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch) Primary Location 702 SW 8TH ST, BENTONVILLE, AR 72716, United States of America Recommended Skills Agile Methodology Algorithms Apache Spark Artificial Intelligence Assessments Cost Reduction Estimated Salary: $20 to $28 per hour based on qualifications.
This role will be focused on operational and execution decision engines with alignment to unified associate signals and workload optimization supported by Retail Science Associate team.
They will be responsible for high level ML/AI conceptualization, feature engineering, ML/AI model development and experimentation, and pilot testing and iterative model refinement.
They will work collaboratively with Product and Tech teams to productionize and scale ML/AI solutions and establish model monitoring and management processes.
This role will require partnership with other teams within the Walmart E2E Fulfillment organization (data governance, science management, retail analytics, customer engine, foundation).
The Principal Data Scientist will play a pivotal in deciding how do we develop ML/AI algorithms, at scale, that are linked to strategic business choices, unified associate signals, efficiency of associate operations, and delivering the desired associate, customer, and/or financial impact.
They own the vision on improving efficiency of data science work streams including prototype development cycle time, model accuracy, model reliability, model stability, coverage of use cases, decisions impact and resources cost savings.
What you'll do:
Apply broad knowledge of ML/AI capabilities to identify growth areas, new and emerging opportunities.
Conducts research by studying organization goals, strategies, practices, and user projects.
Recommends strategies by evaluating organization outcomes; identifying problems; evaluating trends; anticipating requirements.
Influence a team of Data Scientists focused on powering AI/ML solutions within the scope of associate work prioritization, workforce planning and retention strategies.
Partner closely with Data Science Management, Business Leaders, and ML engineering leaders to inform, drive and accelerate innovations in discovery experiences via Insights, frameworks, causal inference solutions and machine learning prototypes.
Execute full life cycle of projects through project planning, data collection, model prototyping and deployment, with responsibilities encompassing stakeholder management and communication to cross-functional partners.
Adhere to MLOps framework to create, build, and deploy data science algorithms continuously test and monitor drifts.
Shares highly complex information related to areas of expertise.
Interacts with senior management to keep abreast of objectives.
Interacts with peers to interpret information and improve cross-functional processes and programs.
Builds and enhances key internal and external contacts.
What you'll bring:
Experience in the development of large-scale ML/AI solutions, Causal Inference and Ranking/Prioritization systems.
6 years
of experience in Applied ML familiar with core supervised and unsupervised algorithms.
Skilled in Programming language (Python) and Large-scale training using data structures and algorithms.
2 years
experience with Causal Inference frameworks, Bayesian Networks and Operations Research methods (Newsvendor problem, Travelling Salesman problem, Shortest Path models, etc.
) Experience with cloud environments including Azure, Google Cloud, etc.
Solid MLOps practices including good design documentation, unit testing, integration testing and source code control (git).
Experienced with agile methodologies using project planning and tracking management tools e.
g.
, JIRA.
Minimum
Qualifications:
Option 1:
Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field.
Option 2:
Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in analytics related field.
Option 3:
8 years' experience in an analytics or related field Preferred
Qualifications:
PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, using open source frameworks (for example, scikit learn, TensorFlow, torch) with 6 years
of experience post graduate degree.
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch) Minimum Qualifications Outlined below are the required minimum qualifications for this position.
If none are listed, there are no minimum qualifications.
Option 1:
Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field.
Option 2:
Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field.
Option 3:
7 years' experience in an analytics or related field Preferred Qualifications Outlined below are the optional preferred qualifications for this position.
If none are listed, there are no preferred qualifications.
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch) Primary Location 702 SW 8TH ST, BENTONVILLE, AR 72716, United States of America Recommended Skills Agile Methodology Algorithms Apache Spark Artificial Intelligence Assessments Cost Reduction Estimated Salary: $20 to $28 per hour based on qualifications.
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