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 Staff Data Scientist to lead the analytics efforts behind our product development. In this role, you will take ownership of 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:
- Create impactful insights and drive Continuous Product Improvement: Provide data-driven recommendations for feature prioritisation, product roadmap adjustments, and iterative product improvements based on insights from user data and experimentation results.
- User Behaviour Analysis: Analyse user behaviour data across multiple platforms to uncover trends, identify friction points, and recommend opportunities for product improvement and innovation.
- Product Experimentation & A/B Testing: Design, execute, and analyse A/B tests and other experimentation methodologies to evaluate product features and enhancements, delivering insights on user preferences and product optimisation.
- Cross-Functional Collaboration: Collaborate with product managers, designers, and engineers to define metrics, track product performance, and ensure that analytics efforts are aligned with strategic product goals.
- Product Metrics & KPIs: 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.
- Data Visualisation & Reporting: Present findings through dashboards, reports, and presentations to both technical and non-technical stakeholders, translating complex data into clear, actionable insights for product teams.
- 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.
- Data Quality & Integrity: Ensure the integrity and accuracy of product data, ensuring that insights are based on reliable and clean datasets.
- Scalable Analytics Solutions: Build and maintain scalable reporting systems and dashboards that track product performance in real time, ensuring accessibility for teams across the organisation.
- Documentation & Knowledge Sharing: Maintain clear documentation of product analytics methodologies, metrics, and insights, facilitating knowledge sharing across product and engineering teams.
- Drive Innovative Ideas: Propose novel solutions and use data story telling to inform product strategy. Shape product strategy and work with key stakeholders.
- Experience with Data modelling and managing an Analytics Pipeline is desirable but not required.
Role Requirements:
- Experience in building and launching AI products and familiarity with ML/ methods
- 3+ years of experience in product analytics, with a strong track record of driving product decisions through data insights.
- Excellent 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.
- In-depth knowledge of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis, etc.
- Experience 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.
- A good understanding of eCommerce industry trends and ecosystems.
- 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.
