Sr. Data Analyst I consulting with stakeholders and leading analytics projects at LexisNexis. Using data tools for insights and mentoring junior analysts to support data-driven decisions.
Responsibilities
Consults with internal stakeholders to clarify business problems, gather requirements, and collect, analyze, and interpret data to support data-driven decisions.
Develops advanced insights and recommendations within their domain.
Uses analytics tools to curate data, build models, create visualizations, and communicate findings to business audiences.
Independently leads high-complexity analytics projects and mentors junior analysts.
Partners with stakeholders to understand business needs and identify the most relevant analyses, KPIs, and success measures.
Supports stakeholders in setting appropriate goals and defining measurable outcomes aligned to business objectives.
Prepares and transforms data using advanced blending, refinement, and quality techniques (including large/complex datasets).
Applies statistical methods and intermediate data models/scenarios to evaluate trends, drivers, and potential outcomes.
Creates clear, compelling data visualizations and narratives tailored to the target audience.
Leads and executes analytics projects independently, including scoping, planning, and managing deliverables to deadlines.
Serves as a subject matter expert within an assigned domain and coaches/mentors junior team members.
Develops working knowledge of adjacent disciplines and how they influence analytics needs and interpretation.
Leverages approved AI tools to accelerate analysis and deliverables while maintaining accountability for accuracy and quality.
Requirements
Bachelor’s or Master’s degree in Data Analytics, Data Science, Mathematics, or a related field; or equivalent practical experience.
3-5 years of relevant experience in analytics, reporting, or data science-adjacent roles.
Strong ability to understand complex data structures and apply advanced data preparation, blending, refinement, and quality techniques (including big data).
Experience applying intermediate statistics to business problems.
Significant experience leveraging SQL and Python for data querying, collection, transformation, and analysis.
Experience with data visualization tools such as Tableau and/or Power BI; ability to design dashboards and narratives for business audiences.
Familiarity with advanced analytics/data platforms (e.g., Databricks or equivalent).
Strong project execution skills: able to structure work into modular tasks, manage multiple projects in parallel, communicate progress, and resolve blockers.
Ability to craft effective prompts, iterate toward higher-quality outputs, and incorporate domain context and constraints.
Benefits
Work in a way that works for you: We promote a healthy work/life balance across the organization.
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