Senior Data Scientist

pbThis position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist based in Belgium. /b /p pThis is a senior, hands-on data science role focused on improving the accuracy and intelligence of a high-volume, real-time identification platform. You’ll work with complex, noisy, and often unlabeled data to develop machine learning approaches that distinguish browsers and devices with greater precision. The role combines advanced machine learning, statistical analysis, experimentation, and backend engineering in a highly technical environment. You’ll own projects from initial research and experimentation through production deployment and integration with real-time services. You’ll also help shape engineering practices, data-driven decision-making, and effective approaches to machine learning across the wider team. This is a fully remote opportunity suited to someone who enjoys solving challenging problems where research, software engineering, and applied ML meet. /p br/ h3Accountabilities /h3 ul lipDevelop data-driven algorithms using raw, noisy, and unlabeled data to improve browser and device identification capabilities. /p /li lipDesign and implement supervised, semi-supervised, and unsupervised machine learning approaches, including methods for high-cardinality categorical data. /p /li lipOwn data science initiatives end to end, from problem definition and experimentation through production deployment and integration with real-time services. /p /li lipDesign experiments and technical solutions for real-time inference, model-to-service integration, training automation, and other machine learning engineering challenges. /p /li lipConduct exploratory data analysis to investigate business and technical questions, identify anomalies, and evaluate model and dataset performance. /p /li lipDevelop practical approaches for collecting and evaluating data when labeled datasets are limited or unavailable. /p /li lipContribute to an engineering-focused, data-driven culture by sharing tools, methodologies, and effective data science practices with colleagues. /p /li lipCollaborate across data science and engineering functions to turn machine learning concepts into reliable, production-ready services. /p /li lipParticipate in a shared on-call rotation, with schedules communicated in advance and coverage designed to minimize disruption outside normal

working hours
. /p /li /ul h3Requirements /h3 ul lip5+ years of professional experience spanning machine learning, data science, and backend development or closely related engineering disciplines. /p /li lipAdvanced knowledge of machine learning fundamentals and statistical methodologies. /p /li lipStrong practical experience with supervised learning, including gradient boosting and approaches for high-cardinality categorical data. /p /li lipHands-on experience with semi-supervised and unsupervised learning techniques. /p /li lipStrong exploratory data analysis and creative problem-solving skills, particularly when working with incomplete, noisy, or unlabeled datasets. /p /li lipProven experience developing real-time machine learning services, including model inference and integration between models and production applications. /p /li lipAbility to transform machine learning models into minimum viable real-time web services and production-ready solutions. /p /li lipExcellent coding and software engineering skills, including strong SQL capabilities and familiarity with Git, CI/CD pipelines, IDEs, and shell scripting. /p /li lipStrong communication skills and fluent English, with the ability to collaborate effectively in a distributed international environment. /p /li lipA research mindset and academic background are advantageous. /p /li lipExperience with Go and backend development is a plus. /p /li lipFamiliarity with analytical data platforms such as ClickHouse, Snowflake, or BigQuery is beneficial. /p /li lipExperience with data transformation frameworks such as dbt, visualization tools such as Superset, Tableau, or Looker, or vector databases such as Pinecone, FAISS, or Qdrant is a plus. /p /li lipExperience building embedding-based search systems is advantageous. /p /li lipFamiliarity with technologies such as Go, SQL, advanced ML frameworks, ClickHouse, dbt, and AWS is beneficial. /p /li /ul h3Benefits /h3 ul lipCompetitive compensation, with the source role indicating a US cash compensation range of b$152,000–$205,000 USD /b; compensation ranges are location-specific and may differ for candidates based in India. /p /li lipFully remote working environment. /p /li lipOpportunity to work on challenging machine learning problems involving real-time systems, large-scale data, and advanced device intelligence. /p /li lipExposure to modern machine learning, data engineering, backend development, and cloud infrastructure technologies. /p /li lipOpportunity to contribute to technical strategy and