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Hypothesis Group Jobs (NOW HIRING)

Hornblower Group

Engineering - Engineer

San Francisco, CA · On-site

$35 - $45/hr

Hornblower Group is a global leader in experience and transportation. Spanning a 100-year history ... Includes formulating likely hypothesis, controlling variables, designing tests, gathering data ...

Sonsoft Inc

Sr. Data Scientist

Memphis, TN

Work on one of following initiatives within Predictive Client Analytics group: RFM recommendations ... Being able to develop hypothesis and test the Hypothesis with careful experiments * Research and ...

Atria Group LLC

UI Developer

Charlotte, NC

$48.75 - $63.50/hr

Concepts of Test and Learn (Hypothesis, KPIs, A/B vs. MVT Testing) * Knowledge of node JS or Angular JS are desirable for future needs (new Advanced Web Frameworks in Nik's organization) * UI skills ...

Point72

Cubist Quantitative Researcher

Chicago, IL · On-site

Successful hires will ultimately become thought leaders within our collaborative research group ... Manage all aspects of the research process, including idea generation, data analysis, hypothesis ...

Point72

Cubist Quantitative Researcher

Seattle, WA

Successful hires will ultimately become thought leaders within our collaborative research group ... Manage all aspects of the research process, including idea generation, data analysis, hypothesis ...

Justrite Safety Group

Paid Media Manager

$90K - $120K/yr

About Justrite Safety Group At Justrite Safety Group, we're more than just a collection of ... Optimize Conversion Funnel KPIs by analyzing the entire funnel, formulating hypothesis and running ...

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Hypothesis Group information

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$37.5K

$122.7K

$196.5K

How much do hypothesis group jobs pay per year?

As of Jun 12, 2026, the average yearly pay for hypothesis group in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

How does a role within the Hypothesis Group typically collaborate with cross-functional teams to drive research projects forward?

In a Hypothesis Group, professionals frequently work alongside data scientists, product managers, engineers, and stakeholders to design, test, and validate business or product hypotheses. Collaboration often involves initial brainstorming sessions, sharing research findings, and iterating on experiments based on interdisciplinary feedback. This dynamic environment encourages open communication, agile methodologies, and regular meetings to ensure alignment and transparency. Effective teamwork helps accelerate discovery, minimize bias, and deliver actionable insights that inform strategic decisions.

What are Hypothesis Groups?

A Hypothesis Group typically refers to a team or collaborative unit that focuses on developing, testing, and validating hypotheses within scientific, research, or data analysis settings. These groups are essential in experimental design and problem-solving as they systematically approach questions or problems by proposing hypotheses and conducting experiments or analyses to confirm or refute them. Hypothesis Groups often work in academic, corporate, or laboratory environments and play a critical role in advancing knowledge and informing decision-making through evidence-based research.

What is the difference between Hypothesis Group vs Data Analyst?

AspectHypothesis GroupData Analyst
Required CredentialsTypically requires a background in marketing, research, or social sciences; often a bachelor's degreeUsually requires a degree in statistics, mathematics, or related fields; often a bachelor's or master's degree
Work EnvironmentCollaborative teams within marketing or research agencies, often project-basedCorporate or consulting settings, working with large datasets and reporting tools
Employer & Industry UsageUsed by marketing agencies, research firms, and product teams to test hypothesesEmployed across industries including finance, healthcare, and tech for data analysis and reporting

Hypothesis Group professionals focus on testing marketing and research hypotheses, often within agency settings, while Data Analysts handle broader data analysis tasks across various industries. Both roles require analytical skills but differ in focus and work environment.

What are the key skills and qualifications needed to thrive as a Market Research Analyst at Hypothesis Group, and why are they important?

To thrive as a Market Research Analyst, you need strong analytical skills, a background in statistics or marketing, and at least a bachelor’s degree in a related field. Proficiency with data analysis tools such as SPSS, Excel, or Tableau, and familiarity with survey platforms are typically required. Exceptional communication, critical thinking, and problem-solving abilities distinguish top performers in this role. These skills ensure accurate data interpretation, actionable insights, and effective client presentations in data-driven environments.
More about Hypothesis Group jobs
What cities are hiring for Hypothesis Group jobs? Cities with the most Hypothesis Group job openings:
What states have the most Hypothesis Group jobs? States with the most job openings for Hypothesis Group jobs include:
What job categories do people searching Hypothesis Group jobs look for? The top searched job categories for Hypothesis Group jobs are:
Hypothesis Group jobs near you
Infographic showing various Hypothesis Group job openings in the United States as of June 2026, with employment types broken down into 4% As Needed, 2% Full Time, 72% Part Time, 2% Temporary, 18% Contract, and 2% Nights. Highlights an 95% Physical, 2% Hybrid, and 3% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Group Product Manager - Data Science

Group Product Manager - Data Science

Dick's Sporting Goods

Remote

Full-time

PTO

Posted 7 days ago

Dick's Sporting Goods rating

6.5

Company rating: 6.5 out of 10

Based on 1,131 frontline employees who took The Breakroom Quiz

15th of 39 rated national retailers

Job description

At DICK'S Sporting Goods, we believe in how positively sports can change lives. On our team, everyone plays a critical role in creating confidence and excitement by personally equipping all athletes to achieve their dreams. We are committed to creating an inclusive and diverse workforce, reflecting the communities we serve.
If you are ready to make a difference as part of the world's greatest sports team, apply to join our team today!
OVERVIEW:
We are looking for a strategic, user-obsessed Group Product Manager to lead DICK'S Sporting Goods' Data Science portfolio. This leader will own the vision, strategy, and execution for data science products that shape experiences and drive measurable business impact across key business priorities.
This role will define the vision for end-to-end Data Science and Machine Learning capabilities, translating business needs into technical delivery across Data Science, ML Engineering, and MLOps. Working closely with Domain and Solution Architects, this leader will drive innovation, automation, and scalable execution across the portfolio. They will also serve as a strategic partner to business and technology leaders, with clear accountability for turning model output into production impact and sustained business value.
This person will lead and coach a team of senior Product Managers and act as a connective leader across Data Science, Engineering, Analytics, Design, and business teams. They must bring strong product judgment, organizational leadership, and technical fluency, with the ability to translate complex machine learning capabilities into clear direction, scalable operating models, and tangible outcomes for users and the business.
Key Responsibilities
  • Define and lead the multi-year vision, strategy, and roadmap for data science products and capabilities.
  • Lead and develop a team of senior Product Managers, setting a high bar for strategic thinking, product rigor, prioritization, and execution excellence.
  • Partner closely with Data Science, ML Engineering, Software Engineering, Analytics, UX, and business teams to translate user and business needs into scalable product solutions.
  • Lead the end-to-end lifecycle of data science products, from opportunity sizing and problem definition through experimentation, launch, activation, adoption, and optimization, ensuring model outputs drive measurable business impact.
  • Partner with Data Science, ML Engineering, and Data Engineering to productionize, scale, deploy, and monitor machine learning models within reliable production pipelines.
  • Establish operating alignment across Data Science teams and platforms to enable consistent model outputs, reusable capabilities, and scalable activation across the portfolio.
  • Advance activation and decisioning capabilities through data science, enabling more precise targeting, personalization, and optimization across channels.
  • Ensure the portfolio delivers measurable value through clear success metrics tied to user experience, engagement, conversion, revenue, efficiency, and ROI.
  • Ensure the portfolio delivers measurable value through clear success metrics tied to forecast accuracy, inventory efficiency, margin improvement, pricing effectiveness, service levels, and operational ROI.
  • Establish a cohesive portfolio strategy across model-driven experiences, decisioning systems, experimentation frameworks, and activation channels.
  • Translate complex machine learning concepts into clear, executive-ready narratives, priorities, and tradeoff decisions for senior stakeholders.
  • Create strong operating mechanisms across teams, including roadmap reviews, backlog prioritization, dependency management, release planning, and alignment to data and technology platform evolution.
  • Deliver data science products against defined OKRs, with clear accountability for impact, timelines, and efficient use of resources.
  • Build strong relationships with business and technology leaders to align on strategy, priorities, and delivery.
  • Influence and develop talent across Data Science, ML Engineering, and Analytics by setting a high bar for product thinking, experimentation rigor, and outcome-driven delivery.
  • Champion a disciplined product management approach to data science, including clear problem framing, hypothesis-driven development, experimentation, and post-launch learning.
  • Partner with legal, privacy, and governance teams to ensure responsible use of data and compliant deployment of data science capabilities.

Relevant Domain Experience
Candidates may bring relevant experience from either customer-facing digital domains or supply chain, merchandising, and operations-focused domains.
Customer-Facing Digital Experience
  • Experience in domains such as eCommerce, Stores, mobile app, search, recommendations, personalization, marketing technology, advertising technology, media, or related customer-facing digital experiences.
  • Familiarity with capabilities such as ranking systems, recommendation systems, audience strategy, decisioning platforms, attribution, campaign optimization, or media effectiveness.
  • Experience applying data science and machine learning to customer experiences, targeting, personalization, discovery, or optimization problems at scale.

Supply Chain, Merchandising, and Operations Experience
  • Experience in domains such as supply chain, merchandising, demand forecasting, pricing, or optimization.
  • Familiarity with capabilities such as demand forecasting, inventory optimization, assortment planning, replenishment, pricing optimization, allocation, or markdown optimization.
  • Experience applying data science and machine learning to forecasting, inventory, pricing, assortment, supply chain, or operational optimization problems at scale.

QUALIFICATIONS:
  • 12 - 15 years of experience in data science, product, or related domains, preferably in data science product management, digital strategy, or technical product leadership.
  • Product management experience with a strong track record of leading complex, data-driven, or machine learning-powered products.
  • Demonstrated ability to lead cross-functional teams spanning Data Science, Engineering, Design, Analytics, and business stakeholders.
  • Deep understanding of experimentation, KPI design, measurement frameworks, and how to evaluate model-driven product performance in production.
  • Strong technical fluency in machine learning concepts, data products, decisioning systems, and applied AI/ML workflows, with the ability to partner effectively with technical teams without needing to be the hands-on builder.
  • Track record of defining strategy, building roadmaps, and delivering measurable business outcomes in fast-paced, highly matrixed environments.
  • Excellent written and verbal communication skills, with the ability to influence executive stakeholders and translate complexity into clear, business-oriented decisions.
  • Bachelor's degree in a relevant field required; advanced degree in business, computer science, engineering, analytics, data science, or a related discipline preferred.

#LI-KF1
VIRTUAL REQUIREMENTS:
At DICK'S, we thrive on innovation and authenticity. That said, to protect the integrity and security of our hiring process, we ask that candidates do not use AI tools (like ChatGPT or others) during interviews or assessments.
To ensure a smooth and secure experience, please note the following:
  • Cameras must be on during all virtual interviews.
  • AI tools are not permitted to be used by the candidateduring any part of the interview process.
  • Offers are contingent upon a satisfactory background check which may include ID verification.

If you have any questions or need accommodations, we're here to help. Thanks for helping us keep the process fair and secure for everyone!
Targeted Pay Range: $114,300.00 - $190,500.00. This is part of a competitive total rewards package that could include other components such as: incentive, equity and benefits. Individual pay is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all teammate pay regularly to ensure competitive and equitable pay.DICK'S Sporting Goods complies with all state paid leave requirements. We also offer a generous suite of benefits. To learn more, visit www.benefityourliferesources.com.

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