SR Data Scientist
for section headings (e.g., About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We should include sections only if posting has real specific content. We have content: DUTIES (responsibilities), REQUIREMENTS (qualifications/skills), Benefits (listed), Pay (pay range), Schedule (hybrid schedule). Also maybe "About the role" could be from intro paragraphs? The intro: "A World-Class Team BJ’s Wholesale Club is powered by more than 30,000 team members..." That's generic company description. Could be considered "About the role"? Might be considered generic but still substantive. However we should avoid filler. The intro is about company culture, not specific role. Might be okay as "About the role". But we need to decide.
We must not repeat job title as heading. Job ID etc not present.
We must remove boilerplate: cookie/navigation/legal/EEO etc. Not present.
We need to preserve all substantive info. So include duties list, requirements list, benefits list, pay, schedule.
We need to use - for any list of duties/requirements/benefits. Use
for prose.
Thus structure:
About the role
... maybe combine the intro paragraphs about BJ's and why you'll love working there? That is substantive but not role-specific. Could be considered "About the role". We'll include that.
Then
Responsibilities
with - each duty bullet.
Then
Requirements
with - each requirement bullet.
Then
Benefits
with - each benefit bullet.
Then
Pay
with containing pay range.
Then
Schedule
with containing schedule description.
We must not include sections with filler like "commensurate with experience". Not present.
We need to ensure we don't include duplicated lines. The posting includes some repeated lines? Not really.
Now extract content.
Intro paragraphs:
"A World-Class Team BJ’s Wholesale Club is powered by more than 30,000 team members who make a real impact every day. Whether you're stocking shelves, solving problems or shaping strategy, your work helps families save on what matters most. We’re a team built on purpose and opportunity. Join us and be part of something meaningful. Why You’ll Love Working at BJ’s At BJ’s Wholesale Club, our team members are at the heart of everything we do. That’s why we offer a comprehensive benefits package designed to support your health, well-being and future – both on and off the job. When you grow, we grow. Here’s just some of what you can look forward to:"
Then benefits list follows.
Thus we could put About the role as first two paragraphs before "Why You’ll Love Working at BJ’s". Actually the "Why You’ll Love Working at BJ’s" leads into benefits. Might be better to treat that as part of Benefits section intro. But we can include About the role as the first paragraph(s) up to "Why You’ll Love Working at BJ’s". Then Benefits section will have the list.
Let's craft About the role:
A World-Class Team BJ’s Wholesale Club is powered by more than 30,000 team members who make a real impact every day. Whether you're stocking shelves, solving problems or shaping strategy, your work helps families save on what matters most. We’re a team built on purpose and opportunity. Join us and be part of something meaningful.
That seems good.
Now Responsibilities: DUTIES list:
- Infrastructure and Deployment (10%): Define infrastructure standards and deployment strategies for machine learning algorithms, including oversight of cluster health, scalability planning, and system monitoring.
- Software Engineering (10%): Oversee the use of collaboration and project management tools (e.g., Jira, Confluence, Git) to ensure consistent project tracking, knowledge sharing, and compliance with internal development standards.
- Collaboration with Data Science and Business Team (25%): Translate business requirements into technical requirements and design data science solutions to support business needs; lead technical discussions with cross-functional teams to align modeling approaches with business objectives; communicate model results, data mining analyses results, and ad hoc analyses with both technical and business teams; mentor junior data scientists and external contractors by reviewing work products and providing technical guidance to support project execution.
- Data Science and Machine Learning (35%): Lead the design and implementation of advanced supervised and unsupervised machine learning solutions using large-scale, distributed data processing platforms; define data science methodologies, modeling strategies, and evaluation frameworks for business problems; oversee the end-to-end lifecycle of machine learning systems, including experimentation, validation, deployment strategy, and post-deployment monitoring.
- Statistical Analysis (20%): Design and direct advanced statistical analyses and data mining approaches, including hypothesis formulation, experimental design, and KPI measurement strategies; identify and interpret key drivers of business outcomes related to member acquisition, engagement, and retention; provide recommendations to senior leadership based on rigorous statistical reasoning and quantitative evidence.
We'll put each as - .
Now Requirements: list items from REQUIREMENTS paragraph. It's a long sentence with semicolons. We need to split into sensible bullet points. The requirement text:
"Master's degree in Data Science, Computer Science, Statistics, or a related field or foreign equivalent and 3 years of experience in data science with a focus on customer and business analytics in retail or technology domains; developing and deploying machine learning models for business applications; building optimization algorithms to solve complex business problems; experience with recommendation engines, customer segmentation, and propensity models; strong programming skills in Python and SQL; machine learning frameworks such as Scikit-learn; statistical techniques and models including regression, clustering, and hypothesis testing; experience applying best practices for managing the machine learning model lifecycle including version control, artifact storage, model registry, and ongoing monitoring and maintenance using industry-standard tools and platforms; exposure to Databricks environment; ability to design and recommend test design strategies for A/B tests using hypothesis testing, clustering, and regression; proficiency in Python libraries including Scikit-learn, Pandas, NumPy, Multiprocessing, Turicreate, and Fuzzywuzzy; experience with linear programming, mixed integer programming, constraint programming, and heuristics using commercial solvers such as Gurobi or open-source solvers such as Google OR-Tools and PuLP. Experience may be gained concurrently"
We'll break each semicolon-separated clause into a bullet.
Thus bullets:
- Master's degree in Data Science, Computer Science, Statistics, or a related field or foreign equivalent and 3 years of experience in data science with a focus on customer and business analytics in retail or technology domains
- Developing and deploying machine learning models for business applications
- Building optimization algorithms to solve complex business problems
- Experience with recommendation engines, customer segmentation, and propensity models
- Strong programming skills in Python and SQL
- Experience with machine learning frameworks such as Scikit-learn
- Knowledge of statistical techniques and models including regression, clustering, and hypothesis testing
- Experience applying best practices for managing the machine learning model lifecycle including version control, artifact storage, model registry, and ongoing monitoring and maintenance using industry-standard tools and platforms
- Exposure to Databricks environment
- Ability to design and recommend test design strategies for A/B tests using hypothesis testing, clustering, and regression
- Proficiency in Python libraries including Scikit-learn, Pandas, NumPy, Multiprocessing, Turicreate, and Fuzzywuzzy
- Experience with linear programming, mixed integer programming, constraint programming, and heuristics using commercial solvers such as Gurobi or open-source solvers such as Google OR-Tools and PuLP
- Experience may be gained concurrently
Now Benefits: list from after "Here’s just some of what you can look forward to:" includes:
- Weekly Pay: Get paid every week so that you can manage your money on your terms.
- Free BJ’s Memberships: Enjoy a complimentary The Club Card Membership, plus a free Supplemental Membership for someone in your household.*
- Generous Paid Time Off: Take the time you need with vacation, personal, sick days, holidays, bereavement, and jury duty leave.*
- Flexible and Affordable Health Benefits: Choose from three medical plans, and access optional dental, vision, Health Savings Account (HSA), and flexible spending account options to fit your lifestyle.*
- 401(k) Retirement Savings Plan: Build your financial future with a company match (available to team members 18 and older).*
- Employee Stock Purchase Plan: Accumulate funds through after-tax payroll deductions that can be used to purchase shares of BJ’s common stock at a 15% discount.*
- Eligibility requirements vary by position.
We'll put each as
- . Note the asterisks maybe footnotes; we keep them.
Now Pay: "The pay range for this position is $150,000 - $175,000". We'll put in
.
Schedule: "This is a hybrid role. Tuesday through Thursday are in-office days at BJ's Club Support Center in Marlborough, MA and Monday and Friday are remote days." We'll put in
.
We must not include any other sections like Qualifications, Skills separately; we have Requirements covering qualifications and skills. Could also add Skills but not needed.
Now produce HTML fragment.
Check for any repeated content: We have not included the "Why You’ll Love Working at BJ’s" paragraph separate; we used only first part. The "Why You’ll Love Working at BJ’s" sentence leads into benefits; we might want to include that as part of Benefits intro? But we already have Benefits list; we could add a
before the list: "At BJ’s Wholesale Club, our team members are at the heart of everything we do. That’s why we offer a comprehensive benefits package designed to support your health, well-being and future – both on and off the job. When you grow, we grow." That is substantive and not duplicated. Let's include that as a
inside Benefits section before the
. That would preserve that content.
Thus Benefits section:
Benefits
At BJ’s Wholesale Club, our team members are at the heart of everything we do. That’s why we offer a comprehensive benefits package designed to support your health, well-being and future – both on and off the job. When you grow, we grow.
- Weekly Pay: Get paid every week so that you can manage your money on your terms.
- Free BJ’s Memberships: Enjoy a complimentary The Club Card Membership, plus a free Supplemental Membership for someone in your household.*
- Generous Paid Time Off: Take the time you need with vacation, personal, sick days, holidays, bereavement, and jury duty leave.*
- Flexible and Affordable Health Benefits: Choose from three medical plans, and access optional dental, vision, Health Savings Account (HSA), and flexible spending account options to fit your lifestyle.*
- 401(k) Retirement Savings Plan: Build your financial future with a company match (available to team members 18 and older).*
- Employee Stock Purchase Plan: Accumulate funds through after-tax payroll deductions that can be used to purchase shares of BJ’s common stock at a 15% discount.*
- Eligibility requirements vary by position.
Now About the role section we already have.
Check for any other substantive content: The line "We recognize the growing role of AI tools, including ChatGPT, and value familiarity with them. That said, we want to hear from your authentic self. Your application should reflect your own skills, experiences, and insights rather than AI-generated responses." This is about
for prose. Thus structure:
About the role
... maybe combine the intro paragraphs about BJ's and why you'll love working there? That is substantive but not role-specific. Could be considered "About the role". We'll include that. Then
Responsibilities
with- each duty bullet.
Then
Requirements
with- each requirement bullet.
Then
Benefits
with- each benefit bullet.
Then
Pay
withcontaining pay range. Then
Schedule
withcontaining schedule description. We must not include sections with filler like "commensurate with experience". Not present. We need to ensure we don't include duplicated lines. The posting includes some repeated lines? Not really. Now extract content. Intro paragraphs: "A World-Class Team BJ’s Wholesale Club is powered by more than 30,000 team members who make a real impact every day. Whether you're stocking shelves, solving problems or shaping strategy, your work helps families save on what matters most. We’re a team built on purpose and opportunity. Join us and be part of something meaningful. Why You’ll Love Working at BJ’s At BJ’s Wholesale Club, our team members are at the heart of everything we do. That’s why we offer a comprehensive benefits package designed to support your health, well-being and future – both on and off the job. When you grow, we grow. Here’s just some of what you can look forward to:" Then benefits list follows. Thus we could put About the role as first two paragraphs before "Why You’ll Love Working at BJ’s". Actually the "Why You’ll Love Working at BJ’s" leads into benefits. Might be better to treat that as part of Benefits section intro. But we can include About the role as the first paragraph(s) up to "Why You’ll Love Working at BJ’s". Then Benefits section will have the list. Let's craft About the role:
A World-Class Team BJ’s Wholesale Club is powered by more than 30,000 team members who make a real impact every day. Whether you're stocking shelves, solving problems or shaping strategy, your work helps families save on what matters most. We’re a team built on purpose and opportunity. Join us and be part of something meaningful.
That seems good. Now Responsibilities: DUTIES list: - Infrastructure and Deployment (10%): Define infrastructure standards and deployment strategies for machine learning algorithms, including oversight of cluster health, scalability planning, and system monitoring. - Software Engineering (10%): Oversee the use of collaboration and project management tools (e.g., Jira, Confluence, Git) to ensure consistent project tracking, knowledge sharing, and compliance with internal development standards. - Collaboration with Data Science and Business Team (25%): Translate business requirements into technical requirements and design data science solutions to support business needs; lead technical discussions with cross-functional teams to align modeling approaches with business objectives; communicate model results, data mining analyses results, and ad hoc analyses with both technical and business teams; mentor junior data scientists and external contractors by reviewing work products and providing technical guidance to support project execution. - Data Science and Machine Learning (35%): Lead the design and implementation of advanced supervised and unsupervised machine learning solutions using large-scale, distributed data processing platforms; define data science methodologies, modeling strategies, and evaluation frameworks for business problems; oversee the end-to-end lifecycle of machine learning systems, including experimentation, validation, deployment strategy, and post-deployment monitoring. - Statistical Analysis (20%): Design and direct advanced statistical analyses and data mining approaches, including hypothesis formulation, experimental design, and KPI measurement strategies; identify and interpret key drivers of business outcomes related to member acquisition, engagement, and retention; provide recommendations to senior leadership based on rigorous statistical reasoning and quantitative evidence. We'll put each as - . Now Requirements: list items from REQUIREMENTS paragraph. It's a long sentence with semicolons. We need to split into sensible bullet points. The requirement text: "Master's degree in Data Science, Computer Science, Statistics, or a related field or foreign equivalent and 3 years of experience in data science with a focus on customer and business analytics in retail or technology domains; developing and deploying machine learning models for business applications; building optimization algorithms to solve complex business problems; experience with recommendation engines, customer segmentation, and propensity models; strong programming skills in Python and SQL; machine learning frameworks such as Scikit-learn; statistical techniques and models including regression, clustering, and hypothesis testing; experience applying best practices for managing the machine learning model lifecycle including version control, artifact storage, model registry, and ongoing monitoring and maintenance using industry-standard tools and platforms; exposure to Databricks environment; ability to design and recommend test design strategies for A/B tests using hypothesis testing, clustering, and regression; proficiency in Python libraries including Scikit-learn, Pandas, NumPy, Multiprocessing, Turicreate, and Fuzzywuzzy; experience with linear programming, mixed integer programming, constraint programming, and heuristics using commercial solvers such as Gurobi or open-source solvers such as Google OR-Tools and PuLP. Experience may be gained concurrently" We'll break each semicolon-separated clause into a bullet. Thus bullets: - Master's degree in Data Science, Computer Science, Statistics, or a related field or foreign equivalent and 3 years of experience in data science with a focus on customer and business analytics in retail or technology domains - Developing and deploying machine learning models for business applications - Building optimization algorithms to solve complex business problems - Experience with recommendation engines, customer segmentation, and propensity models - Strong programming skills in Python and SQL - Experience with machine learning frameworks such as Scikit-learn - Knowledge of statistical techniques and models including regression, clustering, and hypothesis testing - Experience applying best practices for managing the machine learning model lifecycle including version control, artifact storage, model registry, and ongoing monitoring and maintenance using industry-standard tools and platforms - Exposure to Databricks environment - Ability to design and recommend test design strategies for A/B tests using hypothesis testing, clustering, and regression - Proficiency in Python libraries including Scikit-learn, Pandas, NumPy, Multiprocessing, Turicreate, and Fuzzywuzzy - Experience with linear programming, mixed integer programming, constraint programming, and heuristics using commercial solvers such as Gurobi or open-source solvers such as Google OR-Tools and PuLP - Experience may be gained concurrently Now Benefits: list from after "Here’s just some of what you can look forward to:" includes: - Weekly Pay: Get paid every week so that you can manage your money on your terms. - Free BJ’s Memberships: Enjoy a complimentary The Club Card Membership, plus a free Supplemental Membership for someone in your household.* - Generous Paid Time Off: Take the time you need with vacation, personal, sick days, holidays, bereavement, and jury duty leave.* - Flexible and Affordable Health Benefits: Choose from three medical plans, and access optional dental, vision, Health Savings Account (HSA), and flexible spending account options to fit your lifestyle.* - 401(k) Retirement Savings Plan: Build your financial future with a company match (available to team members 18 and older).* - Employee Stock Purchase Plan: Accumulate funds through after-tax payroll deductions that can be used to purchase shares of BJ’s common stock at a 15% discount.* - Eligibility requirements vary by position. We'll put each as
- . Note the asterisks maybe footnotes; we keep them.
Now Pay: "The pay range for this position is $150,000 - $175,000". We'll put in
. Schedule: "This is a hybrid role. Tuesday through Thursday are in-office days at BJ's Club Support Center in Marlborough, MA and Monday and Friday are remote days." We'll put in
. We must not include any other sections like Qualifications, Skills separately; we have Requirements covering qualifications and skills. Could also add Skills but not needed. Now produce HTML fragment. Check for any repeated content: We have not included the "Why You’ll Love Working at BJ’s" paragraph separate; we used only first part. The "Why You’ll Love Working at BJ’s" sentence leads into benefits; we might want to include that as part of Benefits intro? But we already have Benefits list; we could add a
before the list: "At BJ’s Wholesale Club, our team members are at the heart of everything we do. That’s why we offer a comprehensive benefits package designed to support your health, well-being and future – both on and off the job. When you grow, we grow." That is substantive and not duplicated. Let's include that as a
inside Benefits section before the
- . That would preserve that content.
Thus Benefits section:
- Weekly Pay: Get paid every week so that you can manage your money on your terms.
- Free BJ’s Memberships: Enjoy a complimentary The Club Card Membership, plus a free Supplemental Membership for someone in your household.*
- Generous Paid Time Off: Take the time you need with vacation, personal, sick days, holidays, bereavement, and jury duty leave.*
- Flexible and Affordable Health Benefits: Choose from three medical plans, and access optional dental, vision, Health Savings Account (HSA), and flexible spending account options to fit your lifestyle.*
- 401(k) Retirement Savings Plan: Build your financial future with a company match (available to team members 18 and older).*
- Employee Stock Purchase Plan: Accumulate funds through after-tax payroll deductions that can be used to purchase shares of BJ’s common stock at a 15% discount.*
- Eligibility requirements vary by position.
Benefits
At BJ’s Wholesale Club, our team members are at the heart of everything we do. That’s why we offer a comprehensive benefits package designed to support your health, well-being and future – both on and off the job. When you grow, we grow.
- each benefit bullet.
Then
- each requirement bullet.
Then