Senior Data Scientist, Gladly
$134-167k
+ Equity incentive plan
Customer experience AI built for LTV
Job no longer available
Customer experience AI built for LTV
201-500 employees
Job no longer available
$134-167k
+ Equity incentive plan
201-500 employees
Company mission
To make customer service radically personal.
Role
Who you are
- 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
- 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
What the job involves
- 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
- 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
- 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
- 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
Application 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)
Our take
Gladly is a cloud-based platform integrating multiple customer service channels into a single UI. It helps companies cater to the upward trend in personalized service by allowing them to communicate with their customers seamlessly across any channel from voice, email, messaging, chat and social media.
The rise in eCommerce has meant demand for services like Gladly is growing. To stand out, the company has focussed on building out its platform with new features. Most lately, this has included an AI and automation-driven customer service platform.
As a certified app partner to Shopify, Gladly benefits from the ability of Shopify merchants to integrate directly with its platform. The company has raised considerable funding, the latest of which supports accelerated growth on the back of releasing its unified customer service platform.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
15% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Sep 2024
$40m
LATE VC
Dec 2022
$55m
LATE VC
Total funding: $208m
Company benefits
- Stock options
- Medical, Dental, Vision and Life insurance
- Generous paid time off
- Generous paid Parental Leave
- 401K
- Flexible Spending Accounts
- Home office stipends
Company HQ
Bernal Heights, San Francisco, CA
Leadership
Charlie Besecker
(CEO)Charlie joined Gladly in 2024 as a President, moving into the role of CEO in 2025. Prior to this, he was a CRO at GRIN and Route.
Joseph Ansanelli
(Co-Founder & Executive Chairman)After co-founding Gladly in 2015, Joseph served as the CEO until 2025. He has also been at Greylock since 2012, spending 5 years as a General Partner before becoming a Venture Partner.
Andy D'Amato
(CRO)Prior to joining Gladly in 2022, Andy spent nearly 9 years at PTC. While there he held a number of roles, including Senior VP of Sales, Americas IoT & Augmented Reality and Senior VP of Global IoT Sales.
Todd Rakow
(CFO)Todd joined Gladly in 2019 as a VP of FInance & Operations before moving into the role of CFO in 2022. Previously, he co-founded Kanjoya and served as the CFO for nearly 6 years. He also spent some time at PayPal as a Senior Operations & Strategy Manager.
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