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Shopify Data Scientist Jobs (NOW HIRING)

... Shopify, Gartner, Iceland AIR, Arhaus, Thoughtspot, and Postman. By automating complex data ... Data Science, Data Warehouse, Cloud, Analytics, and/or Business Intelligence experience would be ...

Digital Systems Engineer

Somerville, MA · On-site

$188.80K - $223.70K/yr

Responsibilities : • Architect, develop, configure, and customize the back-end Shopify B2B ... data, and API endpoints that serve blazing-fast, SEO-optimized user experiences. • Partner with ...

Digital Systems Engineer

Somerville, MA · On-site

$188.80K - $223.70K/yr

Architect, develop, configure, and customize the back-end Shopify B2B Commerce platform, including ... Partner with the headless front-end teams and provide backend expertise, data, and API endpoints ...

Digital Systems Engineer

Somerville, MA · On-site

$188.80K - $223.70K/yr

Architect, develop, configure, and customize the back-end Shopify B2B Commerce platform, including ... Partner with the headless front-end teams and provide backend expertise, data, and API endpoints ...

Blueprint is methodically built on science. Bryan freely shares his protocol, learnings and data ... Validate data across Shopify, Amazon, Recharge, GA4, Klaviyo, and marketing platforms * Investigate ...

Ecommerce Manager - TN

Waynesboro, TN · On-site

$70K - $90K/yr

We're growing 20% YoY by prioritizing scientific integrity and customer education over typical ... data-driven merchandising practices. What You'll Do Platform Management: Own our Shopify platform ...

Ecommerce Manager - WA

Bellingham, WA · On-site

$70K - $90K/yr

We're growing 20% YoY by prioritizing scientific integrity and customer education over typical ... data-driven merchandising practices. What You'll Do Platform Management: Own our Shopify platform ...

Ecommerce Manager - WA

Bellingham, WA · On-site

$70K - $90K/yr

We're growing 20% YoY by prioritizing scientific integrity and customer education over typical ... data-driven merchandising practices. What You'll Do Platform Management: Own our Shopify platform ...

We're growing 20% YoY by prioritizing scientific integrity and customer education over typical ... data-driven merchandising practices. What You'll Do Platform Management: Own our Shopify platform ...

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Showing results 1-20

Shopify Data Scientist information

See salary details

$46K

$165K

$243.5K

How much do shopify data scientist jobs pay per year?

As of May 30, 2026, the average yearly pay for shopify data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Shopify Data Scientist, and why are they important?

To thrive as a Shopify Data Scientist, you need a strong background in statistics, data analysis, and programming, typically supported by a degree in a quantitative field. Familiarity with tools like Python, SQL, machine learning frameworks, and Shopify’s data platforms is essential. Excellent problem-solving skills, effective communication, and business acumen help translate complex data into actionable insights. These capabilities ensure data-driven decisions that improve Shopify's products and drive business growth.

What are some common challenges faced by Shopify Data Scientists when working with e-commerce data?

Shopify Data Scientists often encounter challenges such as handling large, complex datasets from multiple sources, ensuring data quality, and dealing with incomplete or inconsistent information. They must also design models that can adapt to rapidly changing consumer behaviors and seasonal trends. Collaborating closely with product and engineering teams is essential to align insights with business goals, and there is a continuous need to balance analytical rigor with the fast-paced demands of the e-commerce environment.

What does a Shopify Data Scientist do?

A Shopify Data Scientist analyzes large volumes of data generated by e-commerce stores on the Shopify platform to uncover trends, optimize business strategies, and drive decision-making. They use statistical models, machine learning, and data visualization tools to interpret store performance, customer behavior, and sales patterns. Their insights help improve marketing campaigns, inventory management, and customer experiences. In addition, they collaborate with teams across engineering, product, and marketing to integrate data-driven solutions that enhance the overall performance of Shopify merchants.

What is the difference between Shopify Data Scientist vs Shopify Data Analyst?

AspectShopify Data ScientistShopify Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; experience with machine learningDegree in Analytics, Business, or related field; proficiency in data visualization and reporting tools
Work EnvironmentDevelops predictive models, advanced analytics, machine learning algorithmsPerforms data cleaning, reporting, and basic analysis to support business decisions
Employer & Industry UsageUsed in e-commerce platforms like Shopify for product recommendations, customer segmentationUsed for sales reporting, dashboard creation, and operational insights within Shopify stores

The main difference between a Shopify Data Scientist and a Shopify Data Analyst lies in their focus and skill set. Data Scientists develop complex models and algorithms to predict trends and automate processes, requiring advanced technical skills. Data Analysts focus on interpreting data, creating reports, and providing actionable insights to support business strategies. Both roles are essential in the Shopify ecosystem but serve different analytical needs.

More about Shopify Data Scientist jobs
What cities are hiring for Shopify Data Scientist jobs? Cities with the most Shopify Data Scientist job openings:
What states have the most Shopify Data Scientist jobs? States with the most job openings for Shopify Data Scientist jobs include:
Infographic showing various Shopify Data Scientist job openings in the United States as of May 2026, with employment types broken down into 83% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Senior Director, Sales Engineering

Senior Director, Sales Engineering

Hevo Data

Remote

Full-time

Posted 6 hours ago


Job description

Hevo (www.hevodata.com) is a simple, intuitive, and powerful No-code Data Pipeline platform that enables companies to consolidate data from multiple software for faster analytics.
Hevo powers data analytics for 2000+ data-driven companies across multiple industry verticals, including Shopify, Gartner, Iceland AIR, Arhaus, Thoughtspot, and Postman. By automating complex data integration tasks, Hevo allows data teams to focus on deriving groundbreaking insights and driving their businesses forward.
Hevo's mission is simple, but bold: Build technology that is simple to adopt and easy to access so that everyone can unlock the potential of data.
Headquartered in San Francisco and with offices in India, Hevo has seen exponential growth since its inception. Hevo's revenue and customer base have expanded by a staggering 3X in just the last two years.
With a total funding of $42 Mil from Sequoia India, Qualgro, and Chiratae Ventures, Hevo is now entering a new phase of hyper-growth
Hevoites are a bunch of thoughtful, helpful problem solvers, who are obsessed with making a difference in the lives of their customers, colleagues, and their own individual trajectory.
If you are someone who is passionate about redefining the future of technology, then Hevo is the place for you.
Product Video: https://www.youtube.com/watch?v=p0XGLDgvCo8What
What you'll own in Sales Engineering:
Position Overview:
As the Senior Director of Sales Engineering, you will play a pivotal role in driving the sale of our ELT solutions globally. You will build, train, and lead a global team of high-performing Sales Engineers. You will collaborate closely with the Global Sales and Engineering teams to ensure the seamless delivery of our products and consistent feedback to the product organization.
Understanding Customer Requirements: Work closely with the sales team to comprehend customer needs and execute a Technical Sales process to meet those needs effectively.
Product Demonstrations and Presentations: Conduct engaging product demonstrations, proof of concepts, and technical presentations to showcase our solutions to potential customers.
Technical Leadership: Provide profound technical leadership and guidance to the Sales Engineering team during customer engagements, ensuring clarity and expertise in technical discussions.
Competitive Content: Develop competitive content and playbooks, including ROI calculators and POC Guides, to equip the team.
OKR Tracking: Define and track OKRs such as POC Win Rate, Win Rate, O2C rate, No Opp rate, and Loss Calls, leveraging them as indicators for annual and quarterly strategic planning and driving business growth.
Technical Sales Process Refinement: Refine the technical sales process to ensure competitiveness in the ELT space against key competitors, ensuring consistent success in head-to-head competition.
Team Building and Development:
1 -> Create and deliver content, information, and tools to develop a world-class ELT sales engineering team that can deliver on company goals, including building client relationships, identifying client needs, how our products and services can meet client needs, and capturing opportunities within our accounts.
2 -> Define key processes for POC Requirements, RFP Database, Product feedback, Hiring Requirements, Escalation/Support.
3 -> Build specialized Subject Matter Expertise within the team (e.g. Oracle Log-based CDC, Snow Pro advanced certifications like Architect, Data Engineer, Data Scientist, etc.).
Customer Feedback Management: Collect, synthesize, package, and communicate customer feedback to the Product team, facilitating product improvement and innovation.
Stakeholder Relationship Management: Develop deep, trusting relationships with Sales leadership and cross-functional partners, fostering ongoing communication to assess performance gaps and identify needs.
Pre-sales Process Refinement: Help refine the pre-sales process and methodology, aligning it with the current sales workflow for maximum efficiency and effectiveness.
Sales Enablement Platform Utilization: Leverage sales enablement platforms to deploy, manage, and measure sales engineering training effectively.
What you'll bring to the table:
Technical Expertise:
-> Deep understanding of ETL space.
-> Deep understanding of "Modern Data Stack" analytical architecture, including both batch and streaming interfaces.
-> Deep understanding of Snowflake, BigQuery, Redshift, and Databricks.
-> Deep knowledge of software implementation best practices.
-> Ability to understand complex technical concepts and develop them into a consultative sale.
Qualifications:
-> A bachelor's degree in a technical field; an advanced degree is preferred.
-> 15+ years of experience leading Sales Engineering teams in the data/analytics space.
-> Ability to hire and develop A players.
-> Ability to coach and develop team members.
-> Experience in both a large company and a startup environment.
-> Experience running teams globally.
-> Excellent verbal, written, and in-person communication skills to engage stakeholders at all levels of an organization (individual developer up to CTO).
-> Demonstrated ability to collaborate across teams and functions.
-> Proven track record of meeting and exceeding sales targets.
-> Direct experience working in the SaaS space. Data Science, Data Warehouse, Cloud, Analytics, and/or Business Intelligence experience would be highly preferred.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.