At a Glance
- Tasks: Analyse survey data and develop analytical solutions for market research projects.
- Company: Join Unify, a purpose-driven business at the forefront of research and technology.
- Benefits: Enjoy hybrid work, career progression, and a supportive workplace culture.
- Why this job: Work on exciting projects and contribute to innovative research tools and products.
- Qualifications: Master’s or PhD in relevant fields with experience in survey data analysis.
- Other info: Collaborate with a smart team and stay updated on AI and emerging technologies.
The predicted salary is between 36000 - 60000 £ per year.
Unify is proud to be exclusively representing a fantastic purpose-driven business who are on an incredible journey of growth.
About the Role:
We are looking for a self-starting, analytically sharp Data Scientist / Statistician to join our clients growing team, with a focus on survey data analysis in market research. This is a mid-level position for someone who thrives on solving problems, building robust analytical solutions, and delivering high-quality insights that inform decision-making at the highest level.
In this role, you’ll work on a broad range of exciting projects and be part of a company operating at the cutting edge of research and technology. You’ll have the opportunity not only to carry out sophisticated data analyses but also to play an active role in developing tools, processes, and products that push the boundaries of how data is used in modern research. You’ll report directly to the Head of Technology and Chief Data Scientist, and will be expected to independently interpret briefs, develop analytical strategies, and collaborate with researchers and developers to deliver outstanding results.
Key Responsibilities:
- Perform advanced analysis of survey data from market and social research projects using a range of statistical and data science techniques.
- Interpret briefs from senior stakeholders and independently build out appropriate solutions.
- Apply and develop statistical models (e.g. regression, segmentation, predictive analytics, etc.) and data transformations.
- Collaborate with technical and research teams to develop internal tools, products, and automation pipelines.
- Maintain high standards of data quality, reproducibility, and documentation.
- Communicate findings clearly and effectively to both technical and non-technical audiences.
- Push for analytical excellence and challenge assumptions where necessary.
- Contribute to continuous innovation in methodology, tooling, and analytical approaches.
- Stay current with developments in AI, large language models, and other emerging technologies.
Key Requirements:
- Education: A Master’s or PhD in a relevant discipline (e.g. Sociology, Political Science, Economics, Psychology, Social Policy, Public Health, Marketing) or other social science fields with strong statistical training and survey research components.
- Experience: Demonstrated experience working with survey data in market research, commercial research, or applied social research settings.
- Strong proficiency in R (required) and working knowledge of Python (preferred).
- Familiarity with legacy statistical software such as SPSS, Stata, or SAS is welcome.
- Proven ability to apply inferential statistics and econometric techniques.
- Conduct regression modelling and data wrangling.
- Apply machine learning methods (e.g. clustering, decision trees).
- Work with structured datasets and survey designs.
- Experience or interest in AI and large language models (LLMs) is a plus but not required.
Skills & Attributes:
- Excellent attention to detail and data integrity.
- Strong critical thinking and problem-solving skills.
- Able to work independently and drive projects forward without micromanagement.
- A collaborative team player who can constructively challenge ideas and uphold quality.
- Strong written and verbal communication skills.
- Interest or experience in survey methodology is a plus.
- Passion for learning, growing, and contributing to a high-performance environment.
Why Join this business?
- Work directly on a broad range of exciting projects.
- Join a company at the leading edge of research, technology, and data science.
- Be part of a smart, supportive, and ambitious team that values integrity and innovation.
- Help build the next generation of research tools and products.
- Opportunities for real career progression, learning, and development in AI, analytics, and applied data science.
Benefits include:
- Workplace Culture & Social Perks
- Learning & Development
- Time Off & Flexibility
- Work Life Balance
- Health & Wellness
- Financial Wellbeing
- And SO much more
Sound like you??? Well get involved! Please apply in the first instance by submitting your latest CV for review by our Talent team. Thank you!
Data Scientist employer: Unify Talent - IT, Digital & Tech Recruitment
Contact Detail:
Unify Talent - IT, Digital & Tech Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in survey data analysis and market research. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews, showcasing your passion and knowledge.
✨Tip Number 2
Network with professionals in the field of data science and market research. Attend relevant webinars, workshops, or local meetups to connect with others who can provide insights or even refer you to opportunities within their organisations.
✨Tip Number 3
Brush up on your R and Python skills, as these are crucial for the role. Consider working on personal projects or contributing to open-source projects that involve survey data analysis to demonstrate your capabilities.
✨Tip Number 4
Prepare to discuss specific examples of how you've applied statistical models and data analysis techniques in past roles. Being able to articulate your problem-solving process and the impact of your work will set you apart from other candidates.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and market research. Emphasise your proficiency in R and any experience with Python, as well as your familiarity with statistical software like SPSS or Stata.
Craft a Compelling Cover Letter: Write a cover letter that showcases your analytical skills and problem-solving abilities. Mention specific projects where you've successfully applied statistical models or data analysis techniques, and express your enthusiasm for the role and the company.
Highlight Relevant Education: Clearly state your educational background, especially if you have a Master’s or PhD in a relevant discipline. Include any coursework or projects that involved survey research or statistical training to demonstrate your qualifications.
Showcase Communication Skills: Since the role requires communicating findings to both technical and non-technical audiences, provide examples of how you've effectively communicated complex data insights in previous roles or projects. This could be through presentations, reports, or collaborative work.
How to prepare for a job interview at Unify Talent - IT, Digital & Tech Recruitment
✨Showcase Your Analytical Skills
Prepare to discuss specific examples of how you've applied statistical models and data analysis techniques in previous roles. Be ready to explain your thought process and the impact of your findings on decision-making.
✨Familiarise Yourself with Survey Methodology
Since the role focuses on survey data analysis, brush up on key concepts in survey methodology. Be prepared to discuss how you would approach interpreting briefs and developing analytical strategies based on survey data.
✨Demonstrate Collaboration Experience
Highlight instances where you've worked with cross-functional teams, especially in technical or research settings. Emphasise your ability to communicate complex findings to both technical and non-technical audiences.
✨Stay Current with Emerging Technologies
Research recent developments in AI and large language models. Be ready to discuss how these technologies can enhance data analysis and contribute to innovative solutions in market research.