Data Scientist
Job Details
Hiring Process
Time to Answer
2 open days
Process
1 Phone Call
1 Onsite Interview
Days to get an Offer
4 Days after Interview
Overview
We are seeking an experienced Senior Data Scientist to strengthen a data-driven personalisation team within a digital health ecosystem. The role focuses on evolving recommendation and personalisation capabilities by combining machine learning, experimentation, causal analysis, longitudinal behavioural modelling, and production-grade MLOps. The ideal candidate will help transition from rule-based decision-making to a scalable, measurable, event-driven decision architecture that enables continuous learning and improved member experiences.
Job Responsibilities
- Develop models that capture member behaviour over time, including patterns such as engagement, drop-off, recurrence and churn.
- Build features and modelling approaches using longitudinal and behavioural data.
- Develop, validate and deploy machine-learning models using Python and relevant ML frameworks.
- Evaluate model performance from both a technical perspective and against measurable business and member outcomes.
- Bring machine-learning models safely and reliably into production using AWS-based solutions.
- Implement appropriate model versioning, tracking, monitoring and lifecycle management.
- Contribute to CI/CD pipelines and automated testing for data science and machine-learning components.
- Monitor model and data behaviour in production and help identify performance degradation, data quality issues and model drift.
- Apply sound software-engineering practices to production data science solutions.
- Work closely with Data Scientists, Data Engineers, Product Owners, architects and other stakeholders.
- Perform both business and technical analysis and translate business needs into scalable technical solutions.
- Challenge requirements where needed and contribute actively to solution and architecture discussions.
- Document technical choices, assumptions, experiments and outcomes so that solutions remain understandable and maintainable.
- Contribute to continuous improvement of the team’s data science, experimentation and MLOps practices.
- Design and analyse controlled experiments, including A/B tests and randomised experiments, to evaluate the impact of personalisation and recommendations.
- Define appropriate hypotheses, target groups, outcome metrics and evaluation approaches.
- Apply causal reasoning to distinguish correlation from actual impact and determine which intervention works best for which member or segment.
- Translate experiment results into actionable recommendations for Product Owners and other business stakeholders.
- Contribute to event-driven data flows that capture relevant member interactions, decisions, outcomes and contextual information.
- Help define clear and maintainable event schemas and event-store requirements that preserve the context in which a decision was made.
- Ensure that historical event and decision data can be reliably used for analytics, experimentation and future machine-learning models.
- Work closely with Data Engineers to integrate these patterns into the broader data platform and analytical ecosystem.
Must Have Skills
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Engineering, or a related quantitative field.
- Proven professional experience as a Senior Data Scientist, Machine Learning Engineer, or in a comparable role.
- Strong proficiency in Python and its data science and machine-learning ecosystem.
- Solid understanding of statistics, experimental design and A/B testing.
- Experience developing, evaluating and deploying machine-learning models using real-world data.
- Experience working with behavioural, event-based or time-dependent data.
- Strong understanding of MLOps, including model deployment, versioning, monitoring and lifecycle management.
- Strong knowledge of SQL and experience working with structured and semi-structured data.
- Experience with modern software-development practices, including Git, automated testing and CI/CD.
- Ability to translate business needs into scalable technical solutions and communicate effectively with business and technical stakeholders.
Nice to have
- Experience with configurable rules engines, decision trees or decisioning platforms.
- Experience with AWS services for data and machine-learning workloads, including Amazon SageMaker.
- Experience with data-engineering frameworks such as dbt and/or Dagster.
- Experience with NoSQL databases.
- Experience with Docker and container orchestration such as Kubernetes or Amazon ECS.
- Experience with machine-learning frameworks such as Scikit-learn, PyTorch or TensorFlow.
What's great in the job?
- Great team of smart people, in a friendly and open culture
- Expand your knowledge of various business industries
- Create content that will help our users on a daily basis
- Real responsibilities and challenges in a fast evolving company
Travailler chez yechte
Nous sommes un cabinet de conseil numérique indépendant avec des objectifs ambitieux et une présence mondiale. Nous accompagnons un large éventail d'entreprises, en constituant des équipes numériques et en fournissant des solutions numériques innovantes. Notre personnel multiculturel et diversifié, composé de « citoyens du monde », reflète cette inclusivité.
Nous accordons une grande importance à l'équilibre entre vie professionnelle et vie privée et nous nous efforçons de répondre aux attentes d'une équipe en pleine croissance, en investissant dans les personnes, car elles constituent notre plus grand atout. Notre croissance constante témoigne de cet engagement.
Venez travailler chez yechte, une entreprise en pleine expansion qui offre d'excellents avantages sociaux, des opportunités de développement personnel et la possibilité d'apprendre auprès de leaders accomplis. Nous sommes toujours à la recherche de professionnels exceptionnels pour rejoindre notre équipe.
Ce que nous offrons
Chaque employé a la possibilité de voir l'impact de son travail. Vous travaillez sur de véritables projets numériques et apportez une contribution tangible à l'entreprise. Nous voulons offrir à chacun la possibilité de s'épanouir sur le plan personnel, professionnel et social.
Flexibilité
Votre bien-être nous tient à cœur. Chez yechte, nous proposons des horaires flexibles et des modalités de travail hybrides à domicile/au bureau, améliorant ainsi l'équilibre entre vie professionnelle et vie privée et la productivité des employés.
Avantages attractifs
Votre confort nous tient à cœur. Chez yechte, nous proposons des plans de mobilité économiques et écologiques, des indemnités alimentaires et une couverture santé complète, afin d'améliorer la satisfaction de nos employés.
Développement personnel
Votre épanouissement nous tient à cœur. Chez yechte, nous vous proposons de stimuler votre développement personnel grâce à des formations et des certifications informatiques sur mesure, favorisant une culture d'agilité et d'expertise technologique.
