At a Glance
- Tasks: Use data science to uncover insights and tell compelling stories that drive business decisions.
- Company: Join a leading firm known for its innovative approach to talent analytics.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Other info: Collaborate with diverse teams in a fast-paced environment while advancing your skills.
- Why this job: Make a real impact by transforming data into actionable insights for top executives.
- Qualifications: Experience in data science techniques like text analytics and predictive modelling is essential.
The predicted salary is between 50000 - 70000 £ per year.
The Data Scientist will be responsible for structuring the research question, determining the best analytical approach, conducting analyses, identifying business-relevant insights, and creating a compelling story to be communicated to key stakeholders and talent executive leadership. The person will have expertise in data science, with a strong focus on techniques related to text analytics, clustering, time series analysis, multivariate regression, basic predictive modelling, and significance testing.
Responsibilities
- Utilize data science to conduct research on business topics relevant for digital insights team.
- Use quantitative and qualitative methods to identify new insights on important issues for digital talent team and wider Talent & SL functional teams.
- Identify creative approaches to answer research questions.
- Rapidly test potential approaches.
- Co‑develop research plan.
- Collect and clean data.
- Continuous improvement and creation of predictive modelling taking new levers and environmental factors into account.
- Work on strategic and operational workforce planning modelling.
- Generate innovative analytical ideas by staying up to date on latest tools and methodologies.
- Provide subject matter expertise on key domain‑related topics.
- Enable the best‑fit implementation approach leveraging the core and evolving skills in the domain of data analytics.
- Champion the value of analytics and data‑driven approach across Talent.
- Design data & insights model to cater to data visualization.
- Perform analyses independently.
- Identify insights and communicate findings.
- Use scientific methods and technologies to analyse data, develop models and deliver solutions to the business.
- Data modeling and management, integration and manipulation of large disparate datasets.
- Translate complex analytical results into actionable recommendations.
- Work closely with the Leads across the Digital and wider Talent Functions.
- Develop digital capabilities, define key digital competencies for the team.
- Independently maintain and leverage an internal network.
Qualifications
- Experience applying a broad range of data science techniques.
- Demonstrable understanding of statistics and mathematical concepts relevant to data science.
- Experience with data wrangling, cleansing, and data engineering for data science applications.
- Experience in advanced data visualization tools.
- Ability to participate effectively in virtual teams and networks.
- Strong teaming skills; collaborate effectively across talent ecosystem.
- Strong communication skills for sharing thought leadership.
- Strong organisational skills and attention to detail.
- Strong research and analytical skills.
- Ability to cope with ambiguity.
- Excellent written and verbal communication skills.
- Educated to degree level.
Experience
- Significant experience in a closely related Data analytics / data / insights driven role.
- Experience of developing and implementing operational standards and processes.
- Experience of having worked on digital analytics design/process or analytical planning and development initiatives.
- Demonstrable experience of collaborating with talent colleagues.
- Demonstrable experience of working with third‑party vendors.
- Experience of leading and participating in global dispersed teams.
- Demonstrable experience of working in fast‑paced, ambiguous environments.
- Demonstrable experience of anticipating issues and challenges.
- Experience of conducting internal and external research and analysis.
- Demonstrable experience of having worked to lead or provide SMR advice.
Education
- Educated to degree level.
Certification Requirements
- Higher professional or masters qualification in a related discipline is preferred, not required.
- Active membership in related professional bodies or industry groups is preferred, not required.
To help create the best experience during the recruitment process, please describe any disability‑related adjustments or accommodations you may need.
Data Scientist employer: Ernst & Young
As a Data Scientist at our company, you will thrive in a dynamic and inclusive work culture that champions innovation and collaboration. We offer extensive employee growth opportunities through continuous learning and development, alongside competitive benefits that support your well-being. Located in a vibrant area, our workplace fosters creativity and engagement, making it an excellent environment for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving text analytics and predictive modelling. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and being ready to discuss your analytical approaches. Practice explaining complex concepts in simple terms, as you'll need to communicate insights to non-technical stakeholders.
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative. Tailor your application to highlight your experience with data wrangling and visualisation tools, and let us know how you can contribute to our digital insights team.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Data Scientist role. Highlight your experience with text analytics, clustering, and predictive modelling, as these are key areas we’re looking for. Show us how your skills align with our needs!
Showcase Your Analytical Skills:In your application, don’t just list your skills—demonstrate them! Include specific examples of projects where you’ve used data science techniques to derive insights. We love seeing how you’ve tackled real-world problems with your analytical prowess.
Communicate Clearly:Remember, we need to communicate complex ideas to non-technical audiences. Use clear and concise language in your application. If you can explain your work in a way that’s easy to understand, you’ll stand out to us!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining the StudySmarter team!
How to prepare for a job interview at Ernst & Young
✨Know Your Data Science Techniques
Make sure you brush up on your knowledge of text analytics, clustering, and predictive modelling. Be ready to discuss how you've applied these techniques in past projects, as this will show your expertise and ability to tackle the responsibilities outlined in the job description.
✨Prepare Your Analytical Story
Think about how you can translate complex data insights into a compelling narrative. Practice explaining your findings in simple terms, as you'll need to communicate effectively with non-technical stakeholders. Use examples from your experience to illustrate your points.
✨Showcase Your Technical Skills
Be prepared to demonstrate your proficiency in tools like Python or R during the interview. You might be asked to solve a problem on the spot, so practice coding challenges and be ready to discuss your approach to data wrangling and visualisation.
✨Collaborate and Communicate
Highlight your teamwork skills and your ability to work across diverse teams. Share examples of how you've collaborated with others to achieve results, especially in fast-paced environments. Strong communication is key, so be sure to convey your ideas clearly and confidently.
