Senior Data Scientist-Marketing Analytics

Staples

Framingham (MA)

On-site

USD 140,000 - 190,000

Full time

5 days ago
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Benefits offered by this job

PTO & holidays
Employee discounts
401(k) match
Wellness programs

Job summary

Staples seeks a Senior Data Scientist–Marketing Analytics to design and deploy advanced analytics in a fast-moving retail setting. You will drive marketing measurement, CLV modeling, and personalized recommendations across channels, translating insights into actionable campaigns.

You will lead experimentation, collaborate with marketing, engineering, and leadership, and mentor junior team members while building scalable data assets for cross-functional impact.

Qualifications

  • Bachelor’s Degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or related field.
  • 7+ years of progressively complex experience in data science or related field.
  • Strong understanding of statistical methods (hypothesis testing, regression, model evaluation).
  • Experience with marketing analytics use cases (attribution, campaign measurement, personalization, segmentation).
  • Hands-on experimentation design/analysis (A/B, uplift).
  • Proficiency in Python or R with common libraries (pandas, scikit-learn, TensorFlow, PyTorch).
  • Experience with large datasets and SQL for complex queries and optimization.
  • Independent end-to-end data science project delivery (min 3 projects).
  • Experience communicating technical results to non-technical stakeholders.

Responsibilities

  • Develop and implement marketing measurement solutions (MMM, MTA) to quantify channel performance.
  • Build CLV models to inform acquisition, retention, and investments.
  • Design and deploy personalization and recommendation models for cross-channel engagement.
  • Lead experimentation strategy including A/B and multivariate testing.
  • Partner with marketing to translate analytics into campaigns and optimization plans.
  • Define and measure incremental impact of campaigns and loyalty programs.
  • Create segmentation frameworks using large customer datasets for targeted marketing.
  • Develop reusable data science assets and production-ready solutions.
  • Present insights to stakeholders including senior leadership.

Skills

Analytical thinking
Problem solving
Collaboration
Adaptability
Initiative & ownership
Statistical rigor
Effective communication

Education

Bachelor's in Data Science/Statistics/CS/Engineering/Math
Master's or PhD in related field

Tools

Python
R
SQL
TensorFlow/PyTorch
Spark/Hadoop
AWS/Azure/GCP

Job description

The Senior Data Scientist-Marketing Analytics plays a critical role in designing, developing, and deploying advanced data science and analytics solutions that drive actionable insights and business value. This role applies deep technical expertise and business acumen to solve complex problems, influence decision-making, and improve operational efficiency.

Working on high-impact and often ambiguous initiatives, the Senior Data Scientist-Marketing Analytics independently leads significant components of projects, mentors junior team members, and proactively identifies opportunities for innovation. This role collaborates cross-functionally with business stakeholders, engineering teams, and leadership to translate data into strategic insights and scalable solutions.

What you’ll be doing:
  • Develop and implement advanced marketing measurement solutions, including Marketing Mix Modeling (MMM) and Multi-Touch Attribution (MTA), to quantify channel performance and optimize spend

  • Build and evolve customer lifetime value (CLV) models to inform acquisition, retention, and investment strategies

  • Design and deploy personalization and recommendation models to enhance customer engagement and conversion across channels

  • Lead experimentation strategy, including A/B and multivariate testing, to evaluate marketing initiatives and product features

  • Partner with marketing stakeholders to translate analytical outputs into actionable campaign strategies and optimization plans

  • Define and measure incremental impact (lift) of campaigns, promotions, and loyalty programs

  • Work with large-scale customer and behavioral datasets to create segmentation frameworks that drive targeted marketing and customer experiences

  • Contribute to the development of measurement frameworks across owned, paid, and omnichannel marketing ecosystems

  • Collaborate with data engineering and technology teams to ensure scalable and production-ready solutions.

  • Develop and maintain reusable data science assets, tools, and frameworks to improve efficiency and consistency.

  • Present insights, recommendations, and model outputs to stakeholders, including senior leadership, in a clear and compelling manner

  • Serve as a subject matter expert in selected data science domains (e.g., forecasting, customer analytics, pricing, marketing analytics, optimization)

What you bring to the table:
  • Strong analytical thinking skills, with the ability to break down complex problems, identify key drivers, and translate findings into actionable insight

  • Highly developed problem-solving capabilities, with a proactive approach to identifying challenges and delivering practical, data-driven solutions

  • Collaborative mindset with a track record of working effectively across cross-functional teams and building strong, productive relationships

  • Ability to adapt quickly in a dynamic environment, balancing multiple priorities and adjusting approaches as business needs evolve

  • Demonstrated initiative and ownership, consistently identifying opportunities for improvement and taking action with a sense of urgency and accountability

  • Ability to balance statistical rigor with practical business impact in a fast-paced environment

  • Excellent communication skills, including the ability to clearly explain complex technical concepts to non-technical stakeholders and tailor messaging to different audiences

What’s needed- Basic Qualifications:
  • Bachelor’s Degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, a related field or equivalent work experience.

  • 7+ years of progressively complex related experience in data science or a related field.

  • Strong understanding of statistical methods, including hypothesis testing, regression, and model evaluation techniques

  • Experience with marketing analytics use cases such as attribution, campaign measurement, personalization, or customer segmentation

  • Hands-on experience with experimentation design and analysis (e.g., A/B testing, uplift modeling)

  • Proficiency in Python or R, with demonstrated experience using libraries such as pandas, scikit-learn, TensorFlow, PyTorch, or equivalent

  • Experience working with large datasets using SQL (e.g., writing complex queries, optimizing performance)

  • Demonstrated ability to independently execute end-to-end data science projects (minimum of 3 completed projects with measurable business impact)

  • Experience communicating technical results to non-technical stakeholders (e.g., presentations, dashboards, reports)

What’s needed- Preferred Qualifications:
  • Master’s or PhD in Data Science, Statistics, Computer Science, or a related field

  • 6+ years of experience in advanced analytics, machine learning, or AI

  • Proven track record of leading large-scale data science projects.

  • Experience deploying models into production environments (e.g., APIs, cloud platforms such as AWS, Azure, or GCP)

  • Proficiency with big data technologies (e.g., Spark, Hadoop)

  • Experience with MLOps practices, including model monitoring, versioning, and lifecycle management

  • Domain expertise in areas such as retail, e-commerce, pricing, supply chain, or customer analytics

  • Experience leading project workstreams or mentoring junior team members

  • Demonstrated ability to deliver solutions that resulted in measurable business outcomes (e.g., % revenue uplift, cost savings, efficiency gains)

  • Experience building and deploying Marketing Mix Models (MMM) or Multi-Touch Attribution (MTA) solutions

  • Experience working with customer lifetime value (CLV) modeling and lifecycle analytics

  • Experience developing personalization or recommendation systems in a marketing or e-commerce context

  • Familiarity with causal inference techniques and incrementality measurement frameworks

  • Experience supporting marketing organizations (e.g., paid media, CRM, loyalty, digital analytics)

We Offer:
  • Inclusive culture with associate-led Business Resource Groups

  • 22 days of PTO and Holiday Schedule (7 observed paid holidays + 1 floating holiday)

  • Online and Retail Discounts, Company Match 401(k), Physical and Mental Health Wellness programs, and more!

The salary range represents the expected compensation for this role at the time of posting. The specific base pay may be influenced by a variety of factors to include the candidate's experience, skill set, education, geography, business considerations, and internal equity. In addition to base pay, this role may be eligible for bonuses, or other forms of variable compensation.

Staples is an Equal Opportunity Employer.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender idenity, sexual orientation, age, national origin, protected veteran status, disability, or any other basis protected by federal, state, or local law.

For individuals with disabilities that need additional assistance at any point in the process, please call 1-888-490-4747 for more information.

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