Senior Data Analyst

Job description

Senior Data Analyst Position Overview We are looking for a Senior Data Analyst – Delivery to own end-to-end client data evaluations, from processing and enriching customer datasets to analyzing results and ensuring data quality before delivery. The ideal candidate will have strong experience working with large, complex, and external datasets , with advanced proficiency in SQL and Python . You will analyze match rates, data coverage, quality, and accuracy; identify patterns and gaps; and communicate findings clearly to internal teams and external clients. This role requires strong analytical judgment, attention to detail, and the ability to challenge data and validate results before sharing them with customers. Key Responsibilities Manage client data evaluations end-to-end, including data matching, enrichment, analysis, and delivery. Analyze match rates and data coverage across dimensions such as country, entity size, source, and individual data fields. Investigate data quality issues, inconsistencies, inaccurate matches, missing information, and unreliable confidence scores. Perform thorough QA and validation of datasets before delivering outputs to clients. Prepare clear analysis and documentation explaining methodology, results, data quality, and key findings. Participate in technical discussions with clients and confidently communicate and defend analytical findings. Identify systematic matching failures, coverage gaps, taxonomy issues, and other data quality challenges. Collaborate with Engineering and Data Science teams to communicate findings and recommend product or data improvements. Develop reusable evaluation tools, scoring scripts, evaluation frameworks, and benchmark/golden datasets to improve efficiency. Work with large datasets using Python and SQL, determining when local processing is appropriate and when warehouse-based processing is required. Continuously validate analytical results using multiple approaches to ensure accuracy and reliability. Required Skills & Qualifications 5+ years of professional experience working with complex, real-world, and external datasets. Strong proficiency in SQL and Python , particularly pandas or equivalent data analysis libraries. Experience working with datasets containing millions of records. Strong understanding of data quality, data validation, data analysis, and statistical/analytical methodologies . Practical experience with entity resolution, record linkage, deduplication, data enrichment, or master data management is highly desirable. Ability to analyze and explain precision, recall, match rates, and data coverage . Strong attention to detail and a consistent habit of validating data and analytical results. Excellent written and verbal communication skills. Ability to explain complex analytical findings clearly to technical and non-technical stakeholders. Strong English communication skills, with the ability to participate in technical discussions with international clients. Ability to work independently and take ownership of client-facing deliverables. Preferred Qualifications Experience working with company/firmographic data, corporate data, registry data, or commercial data products . Experience evaluating or working with third-party data vendors. Experience with Apache Spark or similar distributed data-processing technologies . Exposure to industries such as: Insurance Credit Risk Procurement Supply Chain Financial Data Experience working with customer-facing data products or external client datasets. Culture of Belonging: At SSI, we are committed to fostering a culture of belonging where everyone feels valued, respected, and empowered to contribute and grow.