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Data Science Sales Jobs (NOW HIRING)

Gap, Inc.

Senior Analyst, Data Science

Coppell, TX · On-site

$169K - $222K/yr

About the Role Build, validate, deploy, and maintain Data Science and Optimization models ... sales fluctuations; 3. Hands on experience in at least two of the following areas: Inventory ...

Cigna

Data Science Director - Remote

As the Data Science Director for Pricing & Underwriting, you will lead high-impact teams that build ... Partner with pricing, underwriting, actuarial, sales, finance, technology, data engineering, and ...

The Knot Worldwide

VP, Data Science

$235K - $336K/yr

... Marketing, and Sales. RESPONSIBILITIES: Experimentation & Measurement * Define and scale ... Advanced Data Science * Lead applied data science across personalization, marketplace dynamics ...

Cigna

Data Science Director - Remote

Bloomfield, CT · On-site +1

As the Data Science Director for Pricing & Underwriting, you will lead high-impact teams that build ... Partner with pricing, underwriting, actuarial, sales, finance, technology, data engineering, and ...

New

Cigna

Data Science Director - Remote

New York, NY · On-site +1

As the Data Science Director for Pricing & Underwriting, you will lead high-impact teams that build ... Partner with pricing, underwriting, actuarial, sales, finance, technology, data engineering, and ...

New

Cigna

Data Science Director - Remote

Raleigh, NC · On-site +1

As the Data Science Director for Pricing & Underwriting, you will lead high-impact teams that build ... Partner with pricing, underwriting, actuarial, sales, finance, technology, data engineering, and ...

New

Lennar

Sr Manager, Data Science

Miami, FL

Senior Manager, Data Science We are Lennar Lennar is one of the nation's leading homebuilders ... Build durable cross-functional partnerships with Pricing, Sales Operations, Supply Chain, Finance ...

Lennar

Sr Manager, Data Science

Irving, TX

Senior Manager, Data Science We are Lennar Lennar is one of the nation's leading homebuilders ... Build durable cross-functional partnerships with Pricing, Sales Operations, Supply Chain, Finance ...

Lennar

Sr Manager, Data Science

Miami, FL · On-site

Senior Manager, Data Science We are Lennar Lennar is one of the nation's leading homebuilders ... Build durable cross-functional partnerships with Pricing, Sales Operations, Supply Chain, Finance ...

Lennar Homes

Sr Manager, Data Science

Miami, FL · On-site

Senior Manager, Data Science We are Lennar Lennar is one of the nation's leading homebuilders ... Build durable cross-functional partnerships with Pricing, Sales Operations, Supply Chain, Finance ...

XPO

Senior Scientist, Data Science - Hybrid

Boston, MA · On-site

$106K - $132K/yr

Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or any ... Sales, and Finance in order to optimize revenue for the company * Work with a team of data ...

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Data Science Sales information

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How much do data science sales jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for data science sales in the United States is $33.44, according to ZipRecruiter salary data. Most workers in this role earn between $25.96 and $42.31 per hour, depending on experience, location, and employer.

What is the difference between Data Science Sales vs Data Analyst?

AspectData Science SalesData Analyst
Required CredentialsBachelor's degree in Business, Marketing, or related fields; sales experience; knowledge of data productsBachelor's or higher in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentClient-facing, sales meetings, presentations, collaboration with data teamsData exploration, reporting, visualization, working with datasets
Employer & Industry UsageTech companies, consulting firms, data product vendorsFinance, healthcare, marketing, and other industries requiring data insights

Data Science Sales focuses on selling data-driven solutions and products, requiring sales skills and industry knowledge. Data Analysts analyze data to generate insights, requiring technical data skills. While both roles involve data, their core functions and skill sets differ significantly.

How does a Data Science Sales professional typically collaborate with technical teams and clients during the sales process?

In Data Science Sales, professionals frequently act as a bridge between clients and technical teams. They work closely with data scientists and engineers to understand the capabilities and limitations of solutions, ensuring that client requirements are accurately translated into technical deliverables. Throughout the sales cycle, they often participate in client meetings, product demonstrations, and technical discussions, providing clear communication and managing expectations. This collaborative approach helps to build trust, clarify value propositions, and ensure successful project outcomes.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or data. Data scientists often focus on the most impactful features or data subsets to optimize model performance and efficiency.

What are the key skills and qualifications needed to thrive as a Data Science Sales professional, and why are they important?

To thrive as a Data Science Sales professional, you need a solid understanding of data analytics concepts, business acumen, and experience with sales processes, often supported by a relevant bachelor's degree. Familiarity with CRM systems like Salesforce, data visualization tools, and sometimes certifications in analytics or sales methodologies are valuable. Exceptional communication, relationship-building, and problem-solving skills help differentiate top performers in this role. These competencies enable professionals to effectively bridge technical solutions with client needs, driving revenue and long-term partnerships.

Can data scientists make $300k?

Data scientists can earn $300,000 or more annually, especially with extensive experience, advanced skills in machine learning and big data tools, and roles in high-paying industries or senior positions. Achieving this level often requires a combination of expertise, certifications, and sometimes working in competitive markets or consulting roles.

What is the highest paid job in sales?

In sales, executive roles such as Vice President of Sales or Chief Sales Officer tend to be the highest paid, often earning six-figure salaries plus bonuses and commissions. These positions require extensive experience, strategic skills, and leadership abilities, and compensation varies by industry and company size.

What is Data Science Sales?

Data Science Sales refers to the specialized role of selling data science products, solutions, or services to businesses and organizations. Professionals in this field combine technical knowledge of data analytics, machine learning, and AI with strong sales and communication skills to help clients understand the value and applications of data-driven technologies. They identify customer needs, demonstrate how data science can solve business problems, and guide clients through the purchasing process. This role often requires collaboration with technical teams and a deep understanding of both the product and the customer's industry.

Is 40 too late for data science?

Data science is a field open to professionals of all ages, and many successful data scientists start or transition into the role later in their careers. Skills in programming, statistics, and machine learning are more important than age, and continuous learning through online courses or certifications can help late entrants stay competitive.
More about Data Science Sales jobs
What states have the most Data Science Sales jobs? States with the most job openings for Data Science Sales jobs include:
What job categories do people searching Data Science Sales jobs look for? The top searched job categories for Data Science Sales jobs are:
Data Science Sales jobs near you
Infographic showing various Data Science Sales job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $69,552 per year, or $33.4 per hour.

VP of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Posted 4 days ago

Job description

At Forbes Advisor, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance so they can make informed decisions they feel confident in and get back to doing the things they care about most.
We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Forbes Advisor boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Forbes Advisor's global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.
Our Data & Analytics organisation builds the products, platforms and intelligence that power every marketing, product and commercial decision across the business. We're looking for a Data Science leader who believes machine learning only creates value when it changes business decisions.
This is an opportunity to build and lead a commercially driven Data Science function that delivers measurable improvements in customer acquisition, marketing performance and long-term business growth.
You'll lead a growing team of Data Scientists while partnering closely with Engineering, Analytics, Product and Commercial teams to ensure predictive models become trusted, production-ready products that drive measurable commercial outcomes. As we continue investing in first-party data, AI, machine learning and advanced marketing measurement, we're looking for an experienced Data Science leader to help shape the next phase of our commercial Data Science capability.
Responsibilties:
  • Commercial Data Science: Lead the strategy and delivery of predictive models that improve customer acquisition, marketing performance and long-term commercial value. You'll shape capabilities including lifetime value modelling, propensity modelling, customer segmentation, forecasting and value-based bidding, ensuring every model is linked to measurable business outcomes.
  • Marketing Science & Decision Science: Partner with Marketing, Product and Commercial teams to apply Data Science to real business problems. You'll help define how predictive analytics, experimentation and AI improve campaign performance, customer understanding and strategic decision making across platforms including Google and Meta.
  • Production Data Science: Work closely with Engineering and ML Ops to ensure models become reliable, production-ready products rather than one-off analyses. You'll champion reproducible experimentation, scalable deployment, model monitoring, retraining strategies and continuous improvement throughout the model lifecycle.
  • Leadership & Stakeholder Management: Lead and develop a growing team of Data Scientists while building trusted relationships across the business. You'll translate complex modelling into clear commercial recommendations, influence senior stakeholders through evidence, and help establish Data Science as a trusted driver of business strategy and commercial growth.
  • Innovation & Industry Leadership: Represent Forbes in strategic conversations with technology partners including Google and Meta while staying connected to advances in AI, machine learning and marketing science. You'll evaluate emerging technologies, bring new ideas into the organisation and help ensure our Data Science capability remains commercially relevant and technically leading.

Qualifications:
  • Experience leading commercial Data Science, Marketing Science or Decision Science teams.
  • Strong expertise in predictive analytics, customer analytics, machine learning and statistical modelling.
  • Experience applying Data Science to marketing performance, customer acquisition, lifetime value or value-based bidding.
  • Experience productionising machine learning solutions within modern cloud environments and working closely with Engineering and ML Ops teams.
  • Strong understanding of SQL, Python and modern machine learning frameworks.
  • Experience working with Google Ads, Meta or other major advertising platforms.
  • Excellent stakeholder management and communication skills, with the ability to influence both technical and commercial audiences.
  • Experience building and developing high-performing Data Science teams.
  • Strong commercial judgement, balancing technical excellence with measurable business impact.
  • A pragmatic approach to AI, applying emerging technologies where they create genuine commercial value.

Nice to Have
  • Experience within affiliate marketing, digital publishing or lead-generation businesses.
  • Experience working in financial services, insurance or regulated industries.
  • Experience working directly with Google or Meta Data Science teams.
  • Experience with attribution modelling and marketing measurement.
  • Experience building optimisation algorithms for DSPs or advertising platforms.
  • Experience with causal inference, experimentation frameworks or incrementality testing.
  • Experience forecasting marketing or commercial performance.
  • Experience with Vertex AI or equivalent cloud-based machine learning platforms.

Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
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