Gladly, the customer-centered, AI-powered customer support platform is built around people, not tickets. Unlike traditional ticket-based customer support solutions, our software helps brands deliver radically personal service at scale by integrating every channel—voice, email, SMS, chat, social messaging, and self-service—into a single, lifelong conversation stream. Companies like Allbirds, Bombas, Crate & Barrel, and Warby Parker use Gladly to create exceptional customer experiences, transforming everyday customer interactions into lasting connections.

Gladly is a fully distributed company that embraces remote work and believes in flexibility, innovation, and inclusivity. We foster a collaborative, inclusive culture that prioritizes growth, DEIB, and meaningful connections. At Gladly, people are at the heart of everything we do.

About the role & team

Gladly's AI & Research team uses data and insights to power novel AI products and drive data-based decisions across the product team. Data scientists at Gladly partner closely with product managers, engineers and designers to understand our users and innovate on our products using data.

We are looking for someone with the desire and curiosity to learn, take initiative and make a lasting impact at a fast-paced SaaS company.

What you'll do

Collaborate with various Gladly teams and stakeholders to build a deep understanding of our business, our customers and the problems they face
Work closely with our product leadership to influence product roadmap and strategy, driving collaborative discussions based on quantitative insights
Design and perform analyses or experiments to deepen our understanding of customers, uncover product improvement opportunities, provide actionable recommendations, and drive product decisions
Develop novel algorithms to improve customer service automation and Hero efficiency, working on problems from conception through design, prototyping and shipping production features
Provide guidance to other teams about the best practices for gaining insight into product behavior and experimentation to improve product effectiveness
Provide mentorship to other data scientists through code and research reviews, documentation, technical guidance and pairing

You'll be successful by

Being eager to learn Gladly's business domain and customer problems, and applying this knowledge to building innovative products.
Self-organizing and prioritizing your work based on the impact to the customer and business.
Effectively balancing task-based and exploratory work
Being comfortable diving into the data and tracing through product code to understand data origins
Showing ownership and pride in your work by promoting the best practices of building data products within Gladly, educating other teams on their use and providing ongoing maintenance and support.

We're excited about you because you have

5+ years of experience working with data to solve problems and make decisions, especially as a data scientist or product analyst
A strong track record of designing, prototyping, scaling and launching data science products to solve business problems
Excellent SQL and python skills for data manipulation, exploration and visualization, especially in Jupyter notebooks
A strong understanding of ML algorithms
Excellent communication skills; you excel at turning data into compelling and actionable insights and have a proven track record for driving change in a product organization
Customer-centricity and product focus. You look at everything you create through the lens of how it improves experience for the end-user. You are comfortable communicating how various approaches might impact the product behavior (and vice versa).
Learning mentality. You aren't intimidated by new domains or technology; you're willing to dive into documentation/videos, talk to your teammates, and experiment to become well-versed.
Experience working with cross-functional teams including but not limited to Engineering, Design and Product.

How you'll ramp

30 days: Build familiarity with at least one product area and existing data available. Produced at least one new analysis using existing data.
60 days: Comfortable leading discussions with product stakeholders on quantitative analyses and improvement opportunities
90 days: Developed new methods to evaluate and/or algorithms to power AI products that are in production

Interview process

2 hour timed case study
Basic SQL & general programming skills assessment (60 min)
Discussion of a past data science project (60 min)
Experimental design and data interpretation interview (60 min)
Presentation and Q&A (30 min)

Compensation for this role: $134,000 to $167,000 per annum + Equity + Benefits

_The cash compensation above includes base salary, and is not reflective of potential commission for employees in eligible roles, or annual bonus targets under Gladly's bonus plan for eligible roles. In addition to cash compensation, all Gladly's employees are eligible to participate in Gladly's equity incentive plan to receive stock options per the terms of the agreement. Individual compensation packages are based on a few different factors unique to each candidate, including their career level, skills, experience, specific geographic location qualifications and other job-related reasons.

_Why Join Gladly?

At Gladly, we're not just building software—we're transforming an industry. We take a people-first approach, both in our product and our culture. When you join us, you'll enjoy:

Competitive salaries, stock options, and comprehensive benefits
Generous paid time off, parental leave, and home office stipends
A fully remote work environment with opportunities for in-person team gatherings
A strong commitment to professional growth and an inclusive workplace where diverse perspectives thrive

At Gladly, we believe in challenging the status quo, celebrating grit, and striving for excellence. We thrive as a team by embracing transparency, collaboration, and a customer-first mindset. If this role excites you but you don't meet every qualification, we still encourage you to apply. Diverse perspectives and experiences are the cornerstone of our success.