Senior Data Scientist
Styli · Dubai, United Arab Emirates
Apply & track with Apply EdgeRole: Senior Data Scientist
With a strong focus on trendy, affordable fashion and beauty products, STYLI brings over 40,000 styles to men, women, kids, and beauty enthusiasts, offering them the latest global trends delivered directly to their doorsteps.Our vision is to be the most aspirational value fast fashion and lifestyle destination, delivering seamless service excellence. We aim to create personalized experiences, engaging customers across all touchpoints, and continually expanding our curated selection to meet their evolving needs. STYLI has quickly become a leading player in the e-commerce fashion space across the GCC - Saudi Arabia, UAE, Bahrain, and Kuwait and in India.Role overviewWe are looking for a highly motivated, Senior Data Scientist who enjoys solving complex and ambiguous problems using data, statistics and machine learning. You will independently own high-impact Data Science initiatives from problem definition through modelling, experimentation, productionization and impact measurement. You will work closely with Product, Engineering and business stakeholders, while also contributing technical guidance and supporting the development of the wider Data Science team.Key responsibilities● Independently solve complex business and product problems using data, statistics and machine learning.● Own Data Science projects from problem framing and data exploration through modelling, experimentation, deployment and impact measurement.● Extract, clean and analyze large datasets, and design reliable features, training datasets and evaluation frameworks.● Build, evaluate, tune and improve machine-learning, statistical or optimization models using appropriate baselines and metrics.● Conduct detailed error analysis and identify issues related to bias, leakage, data quality and model robustness.● Design and analyze experiments and other measurement approaches to estimate incremental business impact.● Work closely with Product, Engineering and business teams to integrate solutions into production workflows.● Monitor model quality, data health, operational performance and business outcomes after launch.● Make practical trade-offs across accuracy, interpretability, latency, scalability, maintainability and cost.● Write maintainable, reusable, version-controlled and well-documented code.● Communicate findings, recommendations, assumptions and risks clearly to technical and non-technical stakeholders.● Contribute to technical discussions, code and model reviews, and support other Data Scientists when needed. Data Science & AIMust-have skills and experience● Advanced proficiency in Python and SQL, with strong experience building maintainable, reusable and production-oriented Data Science code.● Strong practical experience building, evaluating and deploying machine-learning models, with depth in model selection, experimentation, error analysis and business-impact measurement.● Strong understanding of probability, statistical inference, experimental design and common sources of bias, confounding and data leakage.● Demonstrated experience independently owning multiple Data Science initiatives from problem framing through production and post-launch monitoring.● Experience designing reliable training and evaluation datasets and identifying upstream data-quality or instrumentation gaps.● Working knowledge of production ML concepts, including batch or real-time inference, APIs, CI/CD, model monitoring and retraining.● Ability to make sound technical trade-offs across model quality, latency, scalability, maintainability and infrastructure cost.● Strong stakeholder-management and communication skills, with the ability to influence product and business direction through data and deliver measurable customer or business impact.● A proactive, outcome-oriented mindset with the ability to operate effectively under ambiguity, take ownership without close supervision, and provide constructive technical guidance to others.Good-to-have skills● Strong experience in one or more areas such as recommendation systems, search and ranking, forecasting, pricing, optimization, customer modelling, causal inference, computer vision or generative AI.● Familiarity with distributed processing, orchestration, backend APIs, cloud deployment, search or vector databases, caching technologies and model-serving systems.● Experience in e-commerce, retail, fashion or another large-scale digital product environment.Education and experience● Bachelor's, Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, Operations Research or a related quantitative field.● Typically 5+ years of relevant Data Science or applied machine-learning experience; equivalent depth, scope and demonstrated impact will also be considered.What success looks likeA successful Senior Data Scientist will independently solve complex problems, apply strong technical judgement, deliver reliable production solutions, influence cross-functional decisions and create measurable customer or business impact. Data Science & AI