As a Senior II Data Scientist at Coveo, you will advance data-centric AI innovation and enable data-driven Product decisions through leading experimentation and collaborating with Applied Scientists and Product Managers alike.
At Coveo, we’re not just building AI, we’re operationalizing it at scale. You’ll be at the forefront of that mission, shaping how our AI delivers value and helping world-class brands create experiences that learn and evolve for shoppers and merchandisers.
Here is what makes this opportunity exciting:Our ML team at Coveo focuses on applying the latest advances in Search, GenAI and Recommender Systems to build innovative solutions in e-commerce, self-service and other business verticals.
If you're passionate about combining analytics and machine learning to make a real product impact, join us and help define the future of intelligent commerce!
Here is a glimpse at your responsibilities:- Collaborate with Applied Scientists in building AI features, such as Query Understanding and Learning-to-Rank, through problem scoping, data modelling, predictive analytics and discovery of actionable insights
- Design, run, and interpret controlled online experiments (A/B, multivariate), offline simulations and data analyses to assess the impact of feature and model changes
- Partner with PMs in product feature discovery and roadmap prioritization through validating product hypotheses, designing success metrics and quantifying end user impact
- Initiate and advocate for adoption and best practices in data utilization and experimentation to improve quality and efficiency of the scientific ML lifecycle
- Build analytical solutions to monitor AI product performance and customer impact e.g. self-serve dashboards
- Engage with your community of peers to challenge the status quo, improve our shared ways of working, and influence overall architecture decisions, continuing to foster our culture of Applied Science excellence
- 8+ years of industry experience in data science and analytics or similar role supporting product development or ML research with PhD or MSc in a relevant discipline (ML, Statistics, Physics, Econometrics, etc.)
- Proven ability in data preparation, feature engineering, ML offline evaluation and online experimentation
- Proficiency in conducting data analytics with SQL, Python and BI tools e.g. Looker, Tableau, Metabase
- Exceptional communication skills: you are able to translate complex data into clear, actionable, business-focused narratives
- Experience working in cross-functional teams, collaborating with other scientists, developers and product managers on a daily basis throughout the development lifecycle
- Experience in a technical leadership role: mentoring and coaching, vision and roadmap design, scientific project planning and management, etc
- Experience in SaaS, E-commerce or transactional journey optimization
- Experience with Data/Analytics Engineering stack e.g. dbt, Snowflake
Do you think you can bring this role to life?
You don’t need to check every single box; passion goes a long way and we appreciate that skillsets are transferable.
Send us your CV, we want to get to know you! Join the Coveolife!
We encourage all qualified candidacies regardless of, for example, age, gender, disability, gaps in CV, national or ethnic background. We know that applying for a new role is a lot of work and we really appreciate your time.
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Top Skills
What We Do
Coveo powers the digital experiences of the world’s most innovative brands serving millions of people and billions of interactions across every digital experience. After a decade of enriching our market-leading platform with forward-thinking global enterprises, we know what it takes to gain a trusted AI-experience advantage.
We strongly believe that the future is business-to-person, that experience is today’s competitive front line, a make or break for every business.
For enterprises to achieve this AI-experience advantage at scale, it is imperative to have an Enterprise Spinal and composable ability to deliver AI semantic search and generative experiences at each customer and employee interaction.
