Solutions Engineer

Statsig
London
1 day ago
Create job alert

Who we areAbout Statsig

Statsig is on a mission to fundamentally change how software is built, tested, and shipped. Thousands of companies use Statsig to deploy features safely, run experiments that drive understanding of their customers and business, and analyze user trends to inform their next investment areas. This isnt just about building a better A/B testing tool; this is about catalyzing positive change in how builders build, ultimately resulting in better products and happier customers!

About the Team

Experimentation is Statsig’s marquee product, and serves as the “front door” for most customers onto the Statsig platform. We pride ourselves on having the most advanced product experimentation offering on the market today, available in both a hosted (Statsig Cloud) deployment mode or native to customers’ warehouses (Statsig Warehouse Native).

Statsig’s Experimentation team is constantly working to push the boundaries of product experimentation tooling, integrating cutting-edge statistical methods that enable our customers to run more accurate experiments, faster, and constantly leveling up our experimentation tooling to decrease the friction of scaling experimentation across teams.

What you’ll do

In this role, you will be responsible for providing technical leadership and expertise to our prospects and customers as they adopt and utilize our experimentation platform. You will be the primary technical point of contact for complex customer engagements, helping them understand the value of our product and evangelize utilization to the technology.

The primary responsibilities are to demonstrate the value of the product to prospective customers, identify pain and design solutions for them, lead to successful evaluations in the sales process, and advocate for our customers within the company.

Responsibilities

  • Technical Pre-Sales:

    • Conduct technical discovery calls with prospective customers to understand their specific needs and pain points.

    • Develop and deliver compelling technical presentations and demos that showcase the value proposition of our product suite.

    • Collaborate with sales teams to develop and execute effective sales strategies.

    • Provide technical guidance and support to sales teams throughout the sales cycle.

  • Technical Evangelization:

    • Provide technical leadership and guidance to customers throughout the entire customer journey.

    • Serve as a subject matter expert on our experimentation, feature management, and analytics product suites, its capabilities, and best practices.

    • Conduct technical deep dives, proof of concepts, and troubleshooting sessions to resolve complex issues.

  • Product Expertise & Customer Support:

    • Stay up-to-date with industry trends and emerging technologies.

    • Stay up-to-date on the latest product features and capabilities.

    • Provide feedback to the product team on customer needs and market trends.

    • Contribute to the development of technical documentation and training materials.

    • Work closely with customers to ensure successful deployment and adoption of our platform.

    • Provide technical support and troubleshooting assistance as required.

Who you are

We are seeking a talented and experienced Solutions Engineer to join our team who lives theStatsig valuesand has demonstrated a successful track record in complex solution selling. You are a highly motivated, revenue-oriented individual, looking for an opportunity to help prospects understand how to democratize experimentation, feature management, and product analytics.

Qualifications

  • 2+ years of experience working as a Solutions Engineer / Sales Engineer, selling a technical product to enterprise customers.

  • Led technical proof of concept/proof of value evaluations.

  • Proficient in sales frameworks.

  • Deep knowledge of web technologies, including HTML, CSS, and JavaScript.

  • Familiarity with SQL.

  • Eager to learn new products and help the company improve products continuously.

  • Excellent communication and presentation skills.

  • Ability to work independently and as part of a team.

  • Willingness to collaborate across various US timezones.

Preferred Qualifications

  • Strong understanding of experimentation methodologies.

  • Strong understanding of feature management and processes.

  • Experience with data analysis and visualization tools (e.g., SQL, Python, Tableau).

  • Proficiency in programming languages such as Python.

  • Experience in JavaScript frameworks like React, Next.js, etc.

  • Experience with cloud warehouse tooling (BigQuery, Redshift, Snowflake, Synapse, Firebolt).

  • Knowledge of statistical modeling.

  • Experience with data pipelines and ETL processes.

*While this is a remote role we are currently only considering candidates located in London, UK

Please note that this job description is subject to change and may not include all responsibilities or qualifications required for the role of Solutions Engineer at Statsig.

J-18808-Ljbffr

Related Jobs

View all jobs

Solutions Engineer Sales · London

Solutions Engineering

Senior Solutions Engineer

Senior Solutions Engineer

TECHNICAL SALES ENGINEERS X 5 AI /ML

Technical Sales Engineers / Solutions Engineers – AI & ML

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.