At a Glance
- Tasks: Analyse data to support business decisions and lead complex analytics projects.
- Company: Join a forward-thinking company that values data-driven insights.
- Benefits: Generous holiday, health perks, wellbeing programmes, and learning resources.
- Other info: Dynamic role with opportunities for growth and community involvement.
- Why this job: Make an impact with data while mentoring the next generation of analysts.
- Qualifications: Degree in Data Analytics or related field; experience in analytics and SQL/Python.
The predicted salary is between 55000 - 65000 £ per year.
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 while maintaining accountability for accuracy and quality.
- Develop data products that meet 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 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
- Generous holiday allowance with the option to buy additional days.
- Health screening, eye care vouchers and private medical benefits.
- Wellbeing programs.
- Life assurance.
- Access to a competitive contributory pension scheme.
- Save As You Earn share option scheme.
- Travel season ticket loan.
- Electric vehicle scheme.
- Optional dental insurance.
- Maternity, paternity and shared parental leave.
- Employee assistance programme.
- Access to emergency care for the elderly and children.
- Recares days to support charities and causes.
- Access to employee resource groups with dedicated time to volunteer.
- Access to extensive learning and development resources.
- Access to employee discount scheme via Perks at Work.
Equal Opportunity Statement
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
Global Operations Senior Data Analyst I employer: Limelight Health
As a Global Operations Senior Data Analyst I, you will thrive in a dynamic work environment that champions innovation and collaboration. Our company offers a generous benefits package, including a competitive pension scheme, extensive learning opportunities, and wellbeing programs, all designed to support your professional growth and personal wellbeing. Join us in a culture that values diversity and encourages meaningful contributions, making it an exceptional place to advance your career in data analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Global Operations Senior Data Analyst I
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Global Operations Senior Data Analyst I
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Limelight Health, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Limelight Health. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Limelight Health
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Limelight Health!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.