At a Glance
- Tasks: Dive into data science, analyse trends, and create impactful insights for our digital talent team.
- Company: Join a leading firm that values innovation and collaboration in the tech space.
- Benefits: Enjoy competitive pay, flexible working options, and opportunities for professional growth.
- Other info: Be part of a dynamic team with endless learning opportunities and career advancement.
- Why this job: Make a real difference by transforming data into actionable insights that drive business success.
- Qualifications: Experience in data science techniques and strong analytical skills are 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.
- Use your understanding of what is possible with data science to brainstorm creative analytical solutions to test.
- Rapidly test potential approaches.
- Stand‑up simple analyses to demonstrate what’s possible and test feasibility.
- Co‑develop research plan.
- Work closely with other Digital team members and business stakeholders to help shape the research approach and potential output.
- Collect and clean data.
- Identify relevant data sources (internal and external) and program or leverage existing tools to acquire the data (e.g. SQL, APIs, scrapers, etc.) and test quality.
- Continuous improvement and creation of predictive modelling taking new levers and environmental factors into account.
- Work on strategic and operational workforce planning modelling to enable short‑term and long‑term planning looking at the impact of offshore, automation, and skills while optimising the cost model.
- Generate innovative analytical ideas by staying up to date on latest tools and methodologies.
- Provide subject matter expertise on key domain‑related topics such as advanced Excel, SQL, machine learning, natural language processing, text sentiment analysis, mathematics, statistics, etc.
- Enable the best‑fit implementation approach leveraging the core and evolving skills in the domain of data analytics, e.g., machine learning, natural language processing, text sentiment analysis.
- Champion the value of analytics and data‑driven approach across Talent and provide thought leadership as required on the complete cycle of talent analytics.
- Design data & insights model to cater to data visualization and be accountable for provision of advanced and predictive analytics to deliver robust analyses and support the delivery of insights to the Talent Executive teams.
- Perform analyses.
- Independently conduct rigorous statistical analyses in Python or R.
- Most research projects will utilize quantitative modelling, statistics, or machine learning (especially text analytics).
- Identify insights and communicate findings.
- Create a compelling story that articulates key insights to non‑technical audiences through PowerPoint and/or Business Intelligence Platforms (e.g. PowerBI).
- Uses 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 (i.e., structured, semi‑structured or unstructured).
- Translate complex analytical results into actionable recommendations.
- Work closely with the Leads across the Digital and wider Talent Functions to ensure the provision of services that support business and functional delivery.
- Develop digital capabilities, define key digital competencies for the team, and ensure provision of learning to advance skills.
- Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders across EY practices / functions that will enable personal effectiveness in the position.
Qualifications
- Experience applying a broad range of data science techniques. Key areas include text analytics, clustering, time series analysis, multivariate regression, predictive modelling and significance testing.
- 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 such as Tableau, Spotfire, QlikView and others for integration between disparate data sources, design and implementation of KPIs and generation of automatic and scalable visualisations that will facilitate extraction of business insights.
- Ability to participate effectively in virtual teams and networks across diverse and dispersed geographies.
- Strong teaming skills; collaborate effectively across talent ecosystem, within the digital team and the firm at‑large.
- Strong communication skills for sharing thought leadership across EY and externally to enhance EY reputation.
- Strong organisational skills and attention to detail – the ability to operate within budget and effective time frames.
- Strong research and analytical skills to track and interpret trending directions for data analytics and also to identify potential future options.
- Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment.
- 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 to achieve required outcomes.
- Experience of having worked on digital analytics design/process or analytical planning and development initiatives.
- Experience of developing digital capability, defining key digital competencies for the team, and ensuring provision of learning to advance skills.
- Demonstrable experience of collaborating with talent colleagues to understand needs / requirements and of shaping digital solutions.
- Demonstrable experience of working with third‑party vendors / external system implementors to deliver reporting, insights and analytical solutions from design to enablement.
- Experience of leading and participating in global dispersed teams to enhance services, processes, and standards.
- Demonstrable experience of working in fast‑paced, ambiguous, stressful environments to deliver required results.
- Demonstrable experience of anticipating issues and challenges and proactively working to navigate challenges.
- Experience of conducting internal and external research and analysis, providing best practices and insights to drive improvements.
- Demonstrable experience of having worked to lead or provide SMR advice to achieve successful change outcomes.
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 in City of Westminster 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 in City of Westminster
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving text analytics or predictive modelling. This will give you an edge and demonstrate your expertise to potential employers.
✨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
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes it easier for us to track your application and get back to you quickly.
We think you need these skills to ace Data Scientist in City of Westminster
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 data science techniques like text analytics and predictive modelling, and show how your skills align with what we're looking for.
Showcase Your Projects:Include specific examples of projects you've worked on that demonstrate your analytical skills. Whether it's a clustering project or a time series analysis, we want to see how you've applied your knowledge in real-world scenarios.
Communicate Clearly:When writing your application, keep it clear and concise. Remember, you'll need to communicate complex insights to non-technical audiences, so show us you can do this right from the start!
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 and shows your enthusiasm for 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 key data science techniques like text analytics, clustering, and predictive modelling. Be ready to discuss how you've applied these methods in past projects and how they can be relevant to the role.
✨Prepare Your Storytelling Skills
Since you'll need to communicate complex insights to non-technical stakeholders, practice crafting a compelling narrative around your analyses. Use examples from your experience where you turned data into actionable recommendations that drove business decisions.
✨Familiarise Yourself with Tools
Get comfortable with the tools mentioned in the job description, such as Python, R, and advanced data visualisation platforms like PowerBI. Being able to demonstrate your proficiency with these tools during the interview will show that you're ready to hit the ground running.
✨Showcase Your Collaboration Skills
Highlight your experience working in diverse teams and collaborating with various stakeholders. Prepare examples that illustrate how you've successfully partnered with others to achieve common goals, especially in fast-paced or ambiguous environments.
