Staff Data Scientist

Summary

Join Algolia as a Staff Data Scientist to lead product analytics efforts. You will own product analytics throughout the product lifecycle, from analyzing user behavior to providing actionable recommendations. Leverage data to drive product decisions, collaborate with cross-functional teams, and define key performance indicators. Present findings to stakeholders and ensure data quality and integrity. Build scalable analytics solutions and maintain documentation. Contribute innovative ideas to shape product strategy. The ideal candidate has 3+ years of product analytics experience, strong SQL and Python skills, and a deep understanding of statistical and machine learning models.

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

Responsibilities

• 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

Preferred Qualifications

Experience with Data modelling and managing an Analytics Pipeline is desirable but not required

Benefits

• Algolia’s flexible workplace model is designed to empower all Algolians to fulfill our mission to power search and discovery with ease. We place an emphasis on an individual’s impact, contribution, and output, over their physical location. Algolia is a high-trust environment and many of our team members have the autonomy to choose where they want to work and when
• While we have a global presence with physical offices in Paris, NYC, London, Sydney and Bucharest, we also offer many of our team members the option to work remotely either as fully remote or hybrid-remote employees