At a Glance
- Tasks: Use data science to uncover insights and drive impactful decisions for a global team.
- Company: Join EY, a leader in building a better working world with diverse teams.
- Benefits: Gain future-focused skills, flexible work environment, and a culture of inclusivity.
- Other info: Collaborate globally and enjoy excellent career growth opportunities.
- Why this job: Shape your career while making a real difference through innovative data solutions.
- Qualifications: Experience in data science techniques and strong analytical skills required.
The predicted salary is between 60000 - 80000 € per year.
At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
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:
- 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).
Analytical/Decision Making Responsibilities:
- 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.
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 visualizations 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 organizational 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.
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: At EY, 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.
To help create the best experience during the recruitment process, please describe any disability-related adjustments or accommodations you may need.
EY | Building a better working world. EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
Data Scientist Consultant, Assistant Director in Belgrade employer: EY Société d'Avocats
At EY, we pride ourselves on being an exceptional employer that fosters a culture of inclusivity and innovation. As a Data Scientist Consultant in our vibrant London office, you will benefit from unparalleled opportunities for professional growth, access to cutting-edge technology, and the chance to collaborate with diverse teams across the globe. We are committed to empowering our employees with future-focused skills and a flexible work environment, ensuring that you can thrive while contributing to our mission of building a better working world.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist Consultant, Assistant Director in Belgrade
✨Tip Number 1
Network like a pro! Reach out to current or former EY employees on LinkedIn. Ask them about their experiences and any tips they might have for landing the Data Scientist Consultant role. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for the interview by brushing up on your data science skills. Be ready to discuss techniques like text analytics and predictive modelling. We recommend doing some mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 3
Showcase your analytical prowess! Bring examples of your past work, especially projects that involved clustering or time series analysis. Having tangible evidence of your skills can really impress the interviewers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining EY and shaping a better working world with us.
We think you need these skills to ace Data Scientist Consultant, Assistant Director in Belgrade
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Data Scientist Consultant role. Highlight your experience with data science techniques like text analytics and predictive modelling, and show how your skills align with what EY is looking for.
Showcase Your Analytical Skills:In your application, don’t just list your skills—demonstrate them! Use specific examples of how you've applied data science methods in past projects. This will help us see your problem-solving abilities in action.
Communicate Clearly:Remember, you’ll need to explain complex ideas to non-technical audiences. Use clear and concise language in your application to show that you can communicate effectively, just like you would in a presentation to stakeholders.
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 EY. Plus, it’s super easy!
How to prepare for a job interview at EY Société d'Avocats
✨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 contribute to the team.
✨Craft Your Story
Prepare to articulate your findings in a way that resonates with non-technical audiences. Practice creating compelling narratives around your analyses, as this is crucial for communicating insights effectively to stakeholders.
✨Showcase Your Collaboration Skills
Since teamwork is key in this role, think of examples where you've successfully collaborated with diverse teams. Highlight your ability to work across different functions and how you’ve contributed to achieving common goals.
✨Stay Current with Trends
Demonstrate your passion for data science by discussing recent trends or tools you've been exploring. This shows that you're proactive about continuous learning and can bring innovative ideas to the table.