Senior Data Scientist – Search & Recommendations

Company Description

Accesa is a leading technology company headquartered in Cluj-Napoca, with offices in Oradea and 20 years of experience in turning business challenges into opportunities and growth.

A value-driven organisation, it has established itself as a partner of choice for major brands in Retail, Manufacturing, Finance, and Banking. It covers the complete digital evolution journey of its customers, from ideation and requirements setup to software development and managed services solutions.

With more than 1,200 IT professionals, Accesa also has a fast-growing footprint, establishing itself as an employer of choice for IT professionals who are passionate about problem-solving through technology. Coming together in strong tech teams with a customer-centric approach, they enable businesses to grow, delivering value for our clients, partners, industry, and community.

Responsibilities

Search Analytics & Insights → Analyze large-scale e-commerce search data to identify trends and improvement opportunities across search, ranking, recommendations, and personalization

Query & Ranking Analysis → Investigate search behavior, including zero results, query reformulation, abandonment, position bias, CTR, and relevance versus business trade-offs

KPI Measurement & Experimentation → Define and interpret search KPIs and rigorously evaluate online experiments across ranking, personalization, recommendations, and hybrid or vector search

Data & Metrics Development → Build end-to-end metrics layers using event-level data and server-side search logs, from raw tracking data to clear datasets and visualizations

Cross-Functional Analytical Leadership → Lead analytical initiatives and collaborate with Product, Data Science, MLOps, and ML/Search Engineering teams to improve product and business outcomes

Nice to Have

As a people-first organisation, we believe diversity strengthens our teams and drives innovation. All employment decisions are based on merit, skills, and performance, without discriminating based on any personal characteristic. This reinforces our commitment to providing an inclusive and respectful workplace.

Requirements

Strong hands-on skills in SQL and Python, particularly Pandas, supported by solid statistical knowledge and the ability to create clear data visualizations; Familiarity with the e-commerce search funnel and hands-on experience with query and ranking analysis, including zero results, reformulation, abandonment, position bias, CTR by position, and relevance versus business trade-offs; Experience defining, tracking, and interpreting metrics such as CTR, PDP view rate, add-to-cart, conversion, revenue, and zero-results rate; Experience designing and statistically evaluating ML/search experiments across ranking, personalization, and recommendations; Proficiency with event-level data and server-side search logs, including building multidimensional metrics layers and end-to-end analytical solutions at large e-commerce scale; Proven ability to collaborate with Product Owners, Data Scientists, MLOps, and ML/Search Engineers, lead senior-level initiatives, and deliver measurable product and business impact; Proactive and curious approach to complex problems, with genuine enthusiasm for search, recommendations, ranking, personalization, and AI-powered product discovery; Regular use of AI tools to improve productivity, automate or reduce repetitive work, support decision-making, and deliver higher-quality outcomes; Ability to use AI tools responsibly by structuring effective prompts, critically validating outputs, understanding limitations, and taking ownership of the final result

Nice to have

Experience with GCP, distributed data systems, and analytical databases; Familiarity with offline relevance evaluation metrics: NDCG, Recall@K, MRR and MAP; Knowledge of information retrieval, recommender systems, or ranking models