(USA) Principal, Data Scientist
for sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Remove boilerplate, navigation, legal, EEO, duplicated lines, application instructions. Also do not repeat job title as heading. No markdown fences.
We need to parse the posting.
Key content:
Position Summary... What you'll do...Role summary: We are hiring a Principal Data Scientist to lead the design and development of Walmart Connect's next-generation ads incrementality measurement platform. We are looking for a scientist with rare depth in causal inference, incrementality and RCT experimentation who thrives on doing the hard technical work, not just directing it. You will own the methodology end-to-end, partner with engineering and product to carry solutions into production, and serve as the team's go-to authority on the hardest measurement problems. You will help set the bar for what rigorous, causally grounded ads measurement looks like at Walmart Connect. About the team: The team builds advanced advertising measurement solutions via innovative data science, machine learning and experimentation techniques.
What you'll do: (list items)
- Design and implement large-scale causal inference methodologies to measure the true incremental lift of advertising across campaigns, channels, and segments
- Establish evaluation frameworks, exit criteria, and solution readiness standards causal inference methodologies, grounding approach in hypotheses and data validations (some weird phrasing)
- Author high-quality technical design documents and whitepapers; present to senior leadership
- Define the science roadmap for incrementality and causal measurement; prioritize the highest-leverage problems and make principled trade-offs
- Develop event-grain incrementality models (Uplift DNN) to power ads bidding optimization decisions
- Partner with engineers to design data pipelines and schema that meet the precision requirements of causal measurement at scale
- Mentor senior and mid-level scientists
What you'll bring:
- PhD or Master's in Statistics, Economics, Econometrics, Computer Science, or a related quantitative field — PhD strongly preferred
- 5+ years in data science or quantitative research, ads industry experience preferred
- Deep, specialized expertise in causal inference and/or incrementality-based optimization — Randomized control trials, PIE model, instrumental variables, uplift DNN, regression discontinuity and related methods
- Strong command of experiment design at scale — power analysis, variance reduction, interference and spillover handling, and bias correction
- Proficiency in Python and SQL for large-scale data analysis and experience with distributed data platforms (Spark, BigQuery, or equivalent)
- Strong statistical foundations and machine learning knowledge
Benefits: At Walmart, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more. You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable. For information about PTO, see https://one.walmart.com/notices. Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short-form certificates. Tuition, books, and fees are completely paid for by Walmart. Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms. For Information About Benefits And Eligibility, See One.Walmart.
Pay: Sunnyvale, California US-11658: The annual salary range for this position is $143,000.00 - $286,000.00 Hoboken, New Jersey US-10279: The annual salary range for this position is $132,000.00 - $264,000.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include : Stock
Schedule: Not mentioned; we should not include Schedule section unless present.
We also have Minimum Qualifications and Preferred Qualifications sections but they are basically repeating the "What you'll bring" content. The instructions: Use headings for sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to map content.
"About the role" could be the role summary and about the team. "Responsibilities" = What you'll do list. "Requirements" maybe Minimum Qualifications? "Qualifications" maybe Preferred Qualifications? "Skills" maybe technical skills list? But we can combine.
We must not create sections with filler. We need to include only sections with real specific content.
We have content for About the role (role summary + about team). Responsibilities (list). Requirements (minimum qualifications). Qualifications (preferred qualifications). Skills (maybe proficiency in Python, SQL, etc). Benefits (detailed). Pay (salary ranges). Schedule: none -> omit.
We must avoid repeating job title. Also remove duplicated lines, boilerplate like legal, EEO, etc. Also remove application instructions (none seen). Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate.
We need to output only HTML fragment, no /. Use for each section heading. Use - for any list of duties/requirements/benefits. Use
for prose.
We need to preserve all substantive information; do not invent or summarize away detail.
Let's extract details precisely.
About the role: combine role summary and about the team.
Role summary: "We are hiring a Principal Data Scientist to lead the design and development of Walmart Connect's next-generation ads incrementality measurement platform. We are looking for a scientist with rare depth in causal inference, incrementality and RCT experimentation who thrives on doing the hard technical work, not just directing it. You will own the methodology end-to-end, partner with engineering and product to carry solutions into production, and serve as the team's go-to authority on the hardest measurement problems. You will help set the bar for what rigorous, causally grounded ads measurement looks like at Walmart Connect."
About the team: "The team builds advanced advertising measurement solutions via innovative data science, machine learning and experimentation techniques."
We can combine into a paragraph or two
.
Responsibilities: list items from "What you'll do:" bullet list.
Let's list them exactly:
- Design and implement large-scale causal inference methodologies to measure the true incremental lift of advertising across campaigns, channels, and segments
- Establish evaluation frameworks, exit criteria, and solution readiness standards causal inference methodologies, grounding approach in hypotheses and data validations
- Author high-quality technical design documents and whitepapers; present to senior leadership
- Define the science roadmap for incrementality and causal measurement; prioritize the highest-leverage problems and make principled trade-offs
- Develop event-grain incrementality models (Uplift DNN) to power ads bidding optimization decisions
- Partner with engineers to design data pipelines and schema that meet the precision requirements of causal measurement at scale
- Mentor senior and mid-level scientists
Note second bullet has weird phrasing: "Establish evaluation frameworks, exit criteria, and solution readiness standards causal inference methodologies, grounding approach in hypotheses and data validations". We'll keep as is.
Requirements: Minimum Qualifications section.
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"
We should keep that.
Qualifications: Preferred Qualifications.
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), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture."
We need to keep that.
Skills: Could be the "What you'll bring" list (PhD, experience, expertise, experiment design, proficiency in Python and SQL, strong statistical foundations and ML knowledge). That's more like skills. We'll treat as Skills section.
Benefits: The paragraph about benefits.
Pay: Salary ranges for two locations plus additional compensation.
We need to include both location salary ranges. Keep as prose or list? Probably a
with both.
Schedule: none -> omit.
We must not include headings with empty content.
Now produce HTML.
Structure:
About the role
...
Responsibilities
- ...
...
Requirements
...
Qualifications
...
Skills
- ...
...
Benefits
...
Pay
...
Make sure no extra whitespace? It's fine.
Now extract exact text.
About the role paragraph: combine two sentences.
I'll write:
We are hiring a Principal Data Scientist to lead the design and development of Walmart Connect's next-generation ads incrementality measurement platform. We are looking for a scientist with rare depth in causal inference, incrementality and RCT experimentation who thrives on doing the hard technical work, not just directing it. You will own the methodology end-to-end, partner with engineering and product to carry solutions into production, and serve as the team's go-to authority on the hardest measurement problems. You will help set the bar for what rigorous, causally grounded ads measurement looks like at Walmart Connect. The team builds advanced advertising measurement solutions via innovative data science, machine learning and experimentation techniques.
That's fine.
Responsibilities list: copy each bullet.
Requirements paragraph: include the options.
Qualifications paragraph: include the preferred qualifications text.
Skills list: from "What you'll bring:" bullet list.
Let's extract those bullets exactly:
- PhD or Master's in Statistics, Economics, Econometrics, Computer Science, or a related quantitative field — PhD strongly preferred
- 5+ years in data science or quantitative research , ads industry experience preferred
- Deep, specialized expertise in causal inference and/or incrementality-based optimization — Randomized control trials, PIE model, instrumental variables, uplift DNN, regression discontinuity and related methods
- Strong command of experiment design at scale — power analysis, variance reduction, interference and spillover handling, and bias correction
- Proficiency in Python and SQL for large-scale data analysis and experience with distributed data platforms (Spark, BigQuery, or equivalent)
- Strong statistical foundations and machine learning knowledge
Note there is a stray space before comma
- for any list of duties/requirements/benefits. Use
for prose. We need to preserve all substantive information; do not invent or summarize away detail. Let's extract details precisely. About the role: combine role summary and about the team. Role summary: "We are hiring a Principal Data Scientist to lead the design and development of Walmart Connect's next-generation ads incrementality measurement platform. We are looking for a scientist with rare depth in causal inference, incrementality and RCT experimentation who thrives on doing the hard technical work, not just directing it. You will own the methodology end-to-end, partner with engineering and product to carry solutions into production, and serve as the team's go-to authority on the hardest measurement problems. You will help set the bar for what rigorous, causally grounded ads measurement looks like at Walmart Connect." About the team: "The team builds advanced advertising measurement solutions via innovative data science, machine learning and experimentation techniques." We can combine into a paragraph or two
. Responsibilities: list items from "What you'll do:" bullet list. Let's list them exactly: - Design and implement large-scale causal inference methodologies to measure the true incremental lift of advertising across campaigns, channels, and segments - Establish evaluation frameworks, exit criteria, and solution readiness standards causal inference methodologies, grounding approach in hypotheses and data validations - Author high-quality technical design documents and whitepapers; present to senior leadership - Define the science roadmap for incrementality and causal measurement; prioritize the highest-leverage problems and make principled trade-offs - Develop event-grain incrementality models (Uplift DNN) to power ads bidding optimization decisions - Partner with engineers to design data pipelines and schema that meet the precision requirements of causal measurement at scale - Mentor senior and mid-level scientists Note second bullet has weird phrasing: "Establish evaluation frameworks, exit criteria, and solution readiness standards causal inference methodologies, grounding approach in hypotheses and data validations". We'll keep as is. Requirements: Minimum Qualifications section. 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" We should keep that. Qualifications: Preferred Qualifications. 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), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture." We need to keep that. Skills: Could be the "What you'll bring" list (PhD, experience, expertise, experiment design, proficiency in Python and SQL, strong statistical foundations and ML knowledge). That's more like skills. We'll treat as Skills section. Benefits: The paragraph about benefits. Pay: Salary ranges for two locations plus additional compensation. We need to include both location salary ranges. Keep as prose or list? Probably a
with both. Schedule: none -> omit. We must not include headings with empty content. Now produce HTML. Structure:
About the role
...
Responsibilities
- ... ...
Requirements
...
Qualifications
...
Skills
- ... ...
Benefits
...
Pay
...
Make sure no extra whitespace? It's fine. Now extract exact text. About the role paragraph: combine two sentences. I'll write: We are hiring a Principal Data Scientist to lead the design and development of Walmart Connect's next-generation ads incrementality measurement platform. We are looking for a scientist with rare depth in causal inference, incrementality and RCT experimentation who thrives on doing the hard technical work, not just directing it. You will own the methodology end-to-end, partner with engineering and product to carry solutions into production, and serve as the team's go-to authority on the hardest measurement problems. You will help set the bar for what rigorous, causally grounded ads measurement looks like at Walmart Connect. The team builds advanced advertising measurement solutions via innovative data science, machine learning and experimentation techniques. That's fine. Responsibilities list: copy each bullet. Requirements paragraph: include the options. Qualifications paragraph: include the preferred qualifications text. Skills list: from "What you'll bring:" bullet list. Let's extract those bullets exactly: - PhD or Master's in Statistics, Economics, Econometrics, Computer Science, or a related quantitative field — PhD strongly preferred - 5+ years in data science or quantitative research , ads industry experience preferred - Deep, specialized expertise in causal inference and/or incrementality-based optimization — Randomized control trials, PIE model, instrumental variables, uplift DNN, regression discontinuity and related methods - Strong command of experiment design at scale — power analysis, variance reduction, interference and spillover handling, and bias correction - Proficiency in Python and SQL for large-scale data analysis and experience with distributed data platforms (Spark, BigQuery, or equivalent) - Strong statistical foundations and machine learning knowledge Note there is a stray space before comma