Global Operations Senior Data Analyst I - name

Do you enjoy working with data?

Are you a problem solver?

About our Team: LexisNexis is a data and analytics company with 10,500 colleagues serving customers in more than 150 countries. We’re one of the largest information and analytics companies on the planet. We design solutions that help our customers increase productivity, improve decision-making and outcomes, and be more successful.

About the role: The senior data analyst consults with internal stakeholders to clarify business problems, gather requirements, and collect, analyze, and interpret data to support data-driven decisions. This role develops advanced insights and recommendations within their domain and uses analytics tools to curate data, build models, create visualizations, and communicate findings to business audiences. The Sr. Data Analyst I independently leads high-complexity analytics projects and mentors junior analysts.

Responsibilities

Partner with stakeholders to understand business needs and identify the most relevant analyses, KPIs, and success measures.

Support stakeholders in setting appropriate goals and defining measurable outcomes aligned to business objectives.

Prepare and transform data using advanced blending, refinement, and quality techniques (including large/complex datasets).

Apply statistical methods and intermediate data models/scenarios to evaluate trends, drivers, and potential outcomes.

Create clear, compelling data visualizations and narratives tailored to the target audience.

Lead and execute analytics projects independently, including scoping, planning, and managing deliverables to deadlines.

Serve as a subject matter expert within an assigned domain and coach/mentor junior team members.

Develop working knowledge of adjacent disciplines and how they influence analytics needs and interpretation.

Leverage approved AI tools to accelerate analysis and deliverables (e.g., drafting analyses, summarizing findings, generating code/queries, documenting work) while maintaining accountability for accuracy and quality.

Develops data products that meets the data consumer where they are in their data literacy journey (e.g. chatbot/genie for metrics questions, reusable dashboards).

Requirements:

Bachelor’s or Master’s degree in Data Analytics, Data Science, Mathematics, or a related field; or equivalent practical experience.

Significant experience in analytics, reporting, or data science-adjacent roles.

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 Tab