Senior Data Scientist - Personalisation at Beyond

, , Portugal -

Full Time

Start Date

Immediate

Expiry Date

29 Jan, 26

Salary

0.0

Posted On

31 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Statistical Analysis, Causal Inference, Experimental Design, A/B Testing, Python, SQL, GCP, Algorithm Design, Recommendation Systems, Reinforcement Learning, Data Manipulation, Cloud Computing, Prototyping, Model Development

Industry

IT Services and IT Consulting

Description

Beyond is a technology consultancy helping organizations thrive in a rapidly changing world. We build, modernize, scale, and operationalize technology, creating Cloud and AI solutions to unlock productivity and drive customer growth. Role Overview We're looking for a deeply investigative and creative Senior Data Scientist to uncover opportunities and define the models that power our next generation of intelligent personalization systems. This role is for a true practitioner who is comfortable with ambiguity and excels at translating complex business problems into rigorous, data-driven solutions. You will be the team's expert in algorithmic design and statistical modeling, with a strong focus on prototyping novel approaches for Next Best Action (NBA) and sophisticated feed/collection ranking. You will explore, analyze, and model complex datasets within the GCP ecosystem to validate hypotheses and create the blueprints for production-scale models. What You'll Do: Lead the exploratory analysis and data investigation to identify new features and modeling opportunities for personalization, ranking, and contextual nudges. Design, prototype, and validate a wide range of machine learning models, with a deep focus on algorithms for Next Best Action (NBA) and Learning to Rank (LTR). Apply your expertise in statistical analysis, causal inference, and experimental design to build and interpret robust A/B testing frameworks, ensuring model improvements are statistically significant. Formulate and test hypotheses in an ambiguous problem space, demonstrating a "fail-fast" and iterative approach to model development. Collaborate closely with ML Engineers to define model requirements, feature needs from feature stores, and scalable serving logic. Research and adapt cutting-edge academic techniques in machine learning, recommendation systems, and optimization to solve real-world business challenges. Prototype models for marketing technology use cases, leveraging customer attributes from diverse sources (like Oracle) to prove potential uplift. Communicate complex findings and model mechanics clearly to both technical and non-technical stakeholders. What We're Looking For Advanced degree (MSc or PhD) in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field. 5+ years of hands-on experience as a Data Scientist, applying advanced statistical and machine learning techniques to complex business problems. A deeply investigative and curious mindset, with a proven ability to navigate ambiguous problems and deliver concrete, data-driven insights. Expert-level theoretical and practical knowledge of ML algorithms, including a strong understanding of the mathematics behind models used for ranking (e.g., LTR), recommendations (e.g., collaborative/content filtering, matrix factorization), and decisioning (e.g., uplift modeling, reinforcement learning concepts). Mastery of Python and its core data science/ML ecosystem (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, Jupyter). Strong experience with SQL and data manipulation, ideally within a cloud environment like GCP BigQuery. Experience in designing and analyzing large-scale A/B experiments. A proactive, self-starting mentality and exceptional problem-solving skills. Nice to Have Familiarity with the GCP cloud stack, particularly Vertex AI. Experience with Datadog or other monitoring tools for analyzing model performance. Published research in relevant ML, IR (Information Retrieval), or RecSys (Recommender Systems) conferences. Experience applying LLMs for personalization or search tasks. Experience with reinforcement learning (RL), especially for NBA or dynamic systems. Familiarity with Oracle databases as a data source. Having been named among the Sunday Times Best 100 Companies, we believe culture plays a large role in what we offer as an organization. We actively promote diversity in all its forms across our Studios, and we proudly, passionately, and proactively strive to create a culture of inclusivity and openness for all our employees. Beyond is committed to welcoming everyone, regardless of gender identity, orientation, or expression. Our mission is to remove exclusivity and barriers and encourage new thinking and perceptions in a space of belonging. It is not about race, gender, or age, it is about people. And without our people being their most creative and innovative selves, we are nothing.

Responsibilities

Lead exploratory analysis and data investigation to identify new features and modeling opportunities for personalization. Collaborate closely with ML Engineers to define model requirements and scalable serving logic.