At a Glance
- Tasks: Use data science to uncover insights and tell compelling stories to stakeholders.
- Company: Join a global leader in digital analytics with a focus on innovation.
- Benefits: Flexible work environment, professional development, and a diverse culture.
- Other info: Collaborate with global teams and enhance your skills in a fast-paced environment.
- Why this job: Make an impact by transforming data into actionable insights for talent strategies.
- Qualifications: Experience in data science techniques and strong analytical skills required.
The predicted salary is between 60000 - 80000 ÂŁ 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.
Essential Functions
- Utilise 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 utilise 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).
Analytical/Decision Making Responsibilities
- Uses scientific methods and technologies to analyse data, develop models and deliver solutions to the business.
- Data modelling and management, integration and manipulation of large disparate datasets (i.e. structured, semi‑structured or unstructured).
- Translate complex analytical results into actionable recommendations.
Knowledge and Skills Requirements
- 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 agnostic environment.
Supervision Responsibilities
- 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.
Other Requirements
- Due to global nature of the role; travel and willingness to work alternative hours will be required.
- Due to global nature of the role; English language skills – excellent written and verbal communication will be required.
Job Requirements Education
- Educated to degree level. Higher professional or masters qualification is preferred, not required.
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.
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.
What We Offer You
We’ll develop you with future‑focused skills and equip you with world‑class experiences. We’ll empower you in a flexible environment and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams.
Data Scientist Consultant, Assistant Director in Liverpool employer: EY
Contact Detail:
EY Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist Consultant, Assistant Director in Liverpool
✨Tip Number 1
Network like a pro! Reach out to people in your field on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving text analytics and predictive modelling. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. We recommend simulating the interview environment with a friend to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Data Scientist Consultant, Assistant Director in Liverpool
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with data science techniques like text analytics and predictive modelling. We want to see how your skills align with the role, so don’t hold back on showcasing your relevant projects!
Showcase Your Analytical Skills: When writing your application, emphasise your ability to conduct rigorous statistical analyses and communicate findings effectively. Use examples that demonstrate your expertise in Python or R, and how you've turned complex data into actionable insights.
Be Creative and Innovative: We love seeing candidates who think outside the box! Share any creative approaches you've used to tackle research questions or develop analytical solutions. This will show us your problem-solving skills and your passion for data science.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at EY
✨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 role's responsibilities.
✨Prepare Your Storytelling Skills
Since you'll need to communicate complex insights to non-technical audiences, practice crafting a compelling narrative around your data analyses. Use examples from your experience where you've successfully turned data into actionable recommendations.
✨Familiarise Yourself with Tools
Get comfortable with tools like Python, R, and advanced data visualisation platforms such as PowerBI or Tableau. Be prepared to discuss how you've used these tools to clean data, conduct analyses, and present findings effectively.
✨Show Your Collaborative Spirit
Highlight your experience working in diverse teams and your ability to collaborate across different functions. Share specific examples of how you've partnered with stakeholders to shape research approaches and deliver impactful insights.