At a Glance
- Tasks: Deliver data-driven insights and analytics for clients, transforming complex data into actionable strategies.
- Company: Join a leading firm in data analytics with a focus on innovation and collaboration.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with opportunities to mentor and develop junior talent.
- Why this job: Make a real impact by using data to solve business challenges and drive success.
- Qualifications: Experience in data analytics, strong skills in Python, SQL, and a STEM degree.
The predicted salary is between 55000 - 65000 £ per year.
Responsibilities
- Deliver analytics‑led deal insight for clients, owning defined analytics workstreams within larger assignments.
- Design and deliver high‑quality analysis and insights to meet a range of business needs.
- Develop analytics showcasing the drivers and equity story of a business.
- Create analytics to arm management with data‑driven insights.
- Gather and understand data from multiple sources (e. g., APIs, web data, industry datasets).
- Use Python, SQL, Databricks for data manipulation and analysis.
- Translate technical expertise for non‑technical stakeholders.
- Create reports, dashboards, and presentations, communicating findings effectively.
- Support business development and proposition development for new client problems.
- Raise technical standards by developing reusable analytical approaches, coaching Associates, and contributing to the quality of analytical delivery.
- Act as a business partner and strategic advisor, translating analysis for commercial questions.
Requirements
- Significant relevant experience in data analytics, data science, deals or a related analytical role.
- Degree in a STEM related subject (Science / Technology / Engineering / Mathematics), and a clear interest in how data and technology can be used to solve business problems.
- Strong practical experience using Python, Databricks and/or SQL to manipulate, analyse and interpret datasets, ideally in a professional or client‑facing environment.
- Experience using AI‑enabled tools to accelerate workflow development, improve analytical efficiency and support more scalable analytics delivery.
- Data visualisation and presenting insights in a clear and structured way (e. g. Power BI or similar).
- Experience working with, structuring or combining multiple data sources (including large or complex datasets).
- Experience of coaching / training juniors to support their development.
- Commercial thinking to complex problems, leveraging data analytics to generate insights and support decision‑making.
- An ability to translate data and analysis into clear, commercially relevant insights.
- Strong problem‑solving skills and the ability to approach ambiguous or complex questions.
- Confidence communicating technical concepts to non‑technical stakeholders.
- A proactive approach, with the ability to learn quickly and work effectively as part of a team.
- Flexibility to travel throughout the UK.
- #J-18808-Ljbffr
StudySmarter Expert Advice🤫
We think this is how you could land Senior Associate, Data & Analytics – Deals Insights & Analytics in London
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We think you need these skills to ace Senior Associate, Data & Analytics – Deals Insights & Analytics in London
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 Jobtailor, 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 Jobtailor. 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 Jobtailor
✨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!
✨Showcase Your Projects
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 Jobtailor!
✨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.
