At a Glance
- Tasks: Develop and deploy data science models to enhance client loyalty programmes.
- Company: Join a dynamic start-up using AI to revolutionise retail decisions.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on innovation and learning.
- Why this job: Make a real impact with data science in a fast-paced environment.
- Qualifications: 3+ years in data science, strong Python and SQL skills required.
The predicted salary is between 60000 - 80000 £ per year.
Description
About Us
- We use data science and AI to help retailers make profitable pricing, marketing and retail media decisions.
- Put simply, we help retailers sell the right products, to the right people, for the right price.
- We employ a mix of tech and people to achieve great results for our clients.
- We work with a growing list of household names including; Morrisons, Costa Coffee, Hotel Chocolat, Card Factory, Toolstation, Beaverbrooks and JD Sports.
- Check our website https://hyperfinity. ai/
• Find out why people like to work for Hyper Finity here
Link
The Person
- 3+ years’experience working within data science; Retail/FMCGdata preferable.
- Hands-on experience in extracting and manipulating large data sets in cloud data platforms.
- A self-starter, happy to learn new skills in a self-directed manner.
- Able to quickly adapt to changing requirements as our business grows and expands.
- Keen to work in a start-up environment, and energised by the prospect that the role will be much more varied than in a corporate environment.
- Relevant Degree or equivalent practical experience in a quantitative or computational discipline, with strong foundations in statistics and programming.
The Role
This role is initially aligned to a client operating in Big Query, with the potential to support other client environments over time depending on delivery needs.
- Client-based work; developing, testing and deploying data science models within our client’s data environment to improve the effectiveness of their Customer Loyalty Program.
- Developing prototypes and proof of concepts with rigorous testing approaches to inform further product developments.
- Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress.
- Working in an agile environment.
- Help provide tactical and strategic support to unlock value for our client through data science.
- Ensure good attention to detail with good QC / reconciliation processes in place.
- Collaborate and support immediate team members where required including on client-related topics.
Requirements
Skills and Experience
You will combine strong technical foundations with pragmatic, stakeholder-focused delivery in varied client environments.
- Technical competencies
- Strong analytical and problem-framing skills; able to translate ambiguous business questions into measurable hypotheses and robust analyses/models (necessity).
- Excellent Python and SQL coding skills (necessity).
- Experience working with common Python data/ML libraries (e. g., scikit-learn, pandas, and related tooling) (necessity).
- Experience using version control (e. g., Git) to manage and collaborate on code (necessity).
- Experience working with Big Data and interrogating databases and cloud data platforms (e. g., Big Query, Snowflake, Databricks) (desirable).
- Experience implementing ML in cloud environments (designing scalable data/model workflows within client constraints) (desirable).
- Professional competencies
- Effective communication and listening skills to understand the requirements of the business and present clear recommendations to senior stakeholders (necessity).
- Drive and the resilience to try new ideas if the first approach doesn't work; comfortable working with minimal supervision and maintaining momentum independently (necessity).
- Planning, time management and organisational skills (necessity).
- Strong teamwork and collaboration skills; a proactive approach to sharing ideas, aligning with colleagues, and finding solutions (necessity).
- High attention to detail in analysis and data work (e. g., validating assumptions, checking data quality, and producing reproducible outputs) (necessity).
- Reasonable Adjustments Statement
We want to support you if you need adjustments at any stage of the application process.
To request an adjustment at any stage please let us know some suggestions for adjustments which might help you and / or examples of previous adjustments you’ve found helpful and we’ll do our best to accommodate.
The more detail you can provide us, the more we can help.
Senior Data Scientist in Leeds employer: HyperFinity
At HyperFinity, we pride ourselves on being an exceptional employer that fosters a dynamic and innovative work culture. Our team thrives in a start-up environment where creativity and collaboration are encouraged, offering ample opportunities for personal and professional growth. With a focus on meaningful projects for renowned clients, employees can expect to engage in impactful work while enjoying the flexibility and support needed to excel in their roles.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist in Leeds
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like HyperFinity!
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like HyperFinity.
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We think you need these skills to ace Senior Data Scientist in Leeds
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 HyperFinity, 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 HyperFinity. 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 HyperFinity
✨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 HyperFinity!
✨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.
