Senior Data Scientist – Product Analytics & Machine Learning

ABOUT ALGOLIA 

Algolia is a fast growing company that helps users deliver intuitive search and discovery experiences on their websites and mobile apps. We provide APIs used by thousands of customers in more than 100 countries. Today, Algolia powers 1.5 Trillion searches a year – that’s 4 times more than Bing, Yahoo, DuckDuckGo, Baidu and Yandex combined!

THE MISSION

We are building the next generation of AI powered search products. We make AI explainable and we help customers make data driven decisions through. Work with the product function to guide product development through use of analytics and experimentation. You will be an integral part of building the future of AI search. If you’re passionate about turning product data into actionable insights and driving product success, we’d love to hear from you.

THE OPPORTUNITY

We are seeking a skilled Senior Data Scientist to support the analytics efforts behind our product development. In this role, you will be responsible for product analytics across the entire lifecycle, from gathering and analysing user behaviour data to creating actionable recommendations that drive product decisions. The ideal candidate will have a deep understanding of product analytics, user experience, and the ability to transform data into clear insights that influence product strategy and development. The mission of Data Scientists is to improve customer and business outcomes through better automated decision-making, using Machine Learning and Statistical Modeling.

What you'll be doing:

• Generate actionable product insights: Analyse and aggregate behaviour data to highlight trends, surface friction points and uncover opportunities that improve engagement, retention and conversion by translating findings into clear product recommendations that influence sprint planning and feature prioritisation.
• Design, run and evaluate experiments: Own end-to-end A/B test design, from hypothesis generation and power analysis through to post-test read-outs by partnering with engineering to ensure robust experiment implementation and with product to interpret results and iterate quickly.
• Define and monitor core product metrics: Define, track, and optimise product KPIs (such as user engagement, retention, conversion rates, etc.) to ensure that product improvements are measurable and aligned with business objectives via automated dashboards to make performance visible to teams and leadership by collaborating with Product Managers. 
• User Segmentation & Cohort Analysis: Conduct deep-dive analyses into user cohorts and segments to identify patterns in behaviour and tailor product strategies to different user groups, and recommend tailored product strategies for high-value or at-risk cohorts
• Data Quality & Integrity: Validate tracking implementation, debug data issues and establish checks that guarantee analytical accuracy, and maintain well-documented code, queries and analytical notebooks.
• Contribute to scalable analytics infrastructure: Collaborate with Analytics Engineering to evolve datasets, schemas and pipelines that support self-serve analysis, and develop reusable modelling templates and experiment analysis frameworks.
• Documentation & Knowledge Sharing: Maintain clear documentation of product analytics methodologies, metrics, and insights, facilitating knowledge sharing across product and engineering teams, and craft compelling data stories using visualisations, clear narrative and business context.
• Experience with Data modelling and managing an Analytics Pipeline is desirable but not required. 

Role Requirements:

• Spend 1-2 days per week in a local coworking space to collaborate with your teammates in person.
• Experience in building AI products and familiarity with ML/ methods
• 3+ years of hands-on experience in product analytics or applied data science, ideally within consumer-facing digital products.
• Advanced SQL and Python skills, with a good understanding of best practices in software engineering and data engineering. Familiarity with DBT is a plus. 
• Solid knowledge of statistics: hypothesis testing, confidence intervals, and bootstrap. Strong understanding of experimentation methodologies (A/B testing, multivariate testing, etc.) and their application in product decision-making.
• Sound understanding of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis, etc.
• Familiarity with end-to-end model development and maintenance of ML models used for business-critical decisions.
• Solid understanding of key product metrics such as user engagement, retention, churn, lifetime value, and conversion rates.
• Ability to work with engineering, design, product marketing, GTM sales, and customer support to help launch new products and support existing ones.
• Ability to understand technical business problems, craft effective strategies to tackle them, and present simple solutions to customers.
• Familiarity with search engines and search technologies.
• Detail-oriented, with a focus on data quality and integrity. Great attention to detail while keeping an eye on the big picture.

We’re looking for someone who can live our values:

• GRIT - Problem-solving and perseverance capability in an ever-changing and growing environment
• TRUST - Willingness to trust our co-workers and to take ownership 
• CANDOR - Ability to receive and give constructive feedback.
• CARE - Genuine care about other team members, our clients, and the decisions we make in the company.
• HUMILITY- Aptitude for learning from others, putting ego aside.

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