At a Glance
- Tasks: Lead analytics projects, transforming complex data into actionable insights for clients.
- Company: Join EY-Parthenon, a leader in analytics and AI solutions.
- Benefits: Enjoy competitive salary, flexible work options, and professional growth opportunities.
- Other info: Collaborative environment with mentorship and career advancement potential.
- Why this job: Make a real impact by solving business problems with data and AI.
- Qualifications: 4-7 years in data analytics or engineering; strong communication skills required.
The predicted salary is between 59400 - 72600 £ per year.
EY-Parthenon is seeking a motivated Manager to join its Analytics & AI practice, supporting clients to unlock value from data through analytics, reporting, AI and data-driven insights.
This role is ideal for an individual with a strong commercial and technical mindset who enjoys solving business problems using data and is looking to develop both consulting and technical expertise.
Managers work across a variety of strategic engagements across the deal lifecycle helping clients make informed business decisions by transforming complex data into actionable insights.
Working alongside experienced consultants, managers and senior leaders, you will design and deliver high-quality analytics solutions, develop meaningful business insights and communicate findings confidently to both technical and non-technical stakeholders., Client Delivery
- Client Delivery
- Lead day-to-day activities throughout the life-cycle of an assignment - requirements definition, specification, data collection, solution design, development, testing, documentation, implementation, and user training
- Work directly with clients as well as other EY specialist teams to develop formal deliverables for clients including data dashboards (Excel or other data visualisation tools), web hosted solutions, Word reports, and Power Point presentations
- Explain complex technical concepts underpinning your analysis in simple terms to clients to help them understand how their business needs are being addressed
- Identify risk on the assignment, involving Director / Partner appropriately in its resolution
- Analytics & AI Solutions
- Design and build complex database models and insightful visualisation dashboards to perform analysis on large diverse datasets
- Leading a team in designing analytical solutions (data pipelines, visualisations, machine learning models), undertaking proof-of-concepts, and implementing these solutions to help clients to compete effectively in this dynamic environment with the support of Directors and Partners
- Work with structured and unstructured data to identify trends, patterns and key findings
- Build scalable, reliable and fit-for-purpose data models, datasets and reporting solutions
- Conduct data quality assessments and validation activities to ensure analytical outputs are accurate and reliable
- Contribute to innovation initiatives and proof-of-concepts exploring emerging analytics, machine learning and AI capabilities
- Support the implementation of advanced analytical and AI-driven solutions where appropriate
- Stakeholder Engagement
- Communicate analytical findings clearly and effectively to technical and non-technical audiences
- Participate in client meetings, workshops and working sessions
- Build strong working relationships with clients, colleagues and wider EY teams.
- Manage stakeholder expectations regarding deliverables, timelines and project outcomes
- Continuously seek feedback and identify opportunities to improve deliverable quality and client service
- Team & Personal Development
- Take ownership of your team's tasks and work with junior team members and help develop their skills and technical expertise
- Collaborate effectively with colleagues across different grades and service lines
- Support, mentor, and train junior team members where appropriate
- Take ownership of personal development and continuously build technical, commercial, and consulting skills
- Stay informed on developments in analytics, AI, data management and emerging technologies
- Core Experience
- Approximately 4-7 years experience in data engineering, data analytics, or related fields, ideally in a consulting or in-house strategy environment
- Exposure to transaction support, value creation or fast-paced delivery environments is beneficial
- Experience applying data and analytics to solve business problems in financial, operational or commercial environments
- Experience gained within consulting, professional services, finance, FP&A, transaction services or analytics-focused teams is highly desirable
- Consulting & Communication Skills
- Ability to work with clients and deliverable users, identify their particular use case requirements, design appropriate solutions to load data, perform complex calculations, derive outputs and deliver interface tools to provide repeatable visual output
- Strong business acumen and technical knowledge to translate commercial problem into data requirement and formulate analytics solution
- Excellent oral and written communication skills - including experience of writing reports, drafting presentations and developing data visualisation dashboards to effectively communicate advice to clients
- Capability to communicate the business and non-technical implications of technical roadblocks and technical design decisions to non-technical clients
- Ability to structure ambiguous business problems and develop data-driven recommendations
- Experience working with large, complex datasets to communicate trends, patterns, anomalies, and business insights
- Ability to communicate effectively with both business and technical stakeholders
Technical Skills We value individuals who can learn quickly and apply the right approach to solve business challenges.
- SQL and Python or R
- Building and maintaining data pipelines and analytical workflows
- Visually creative, with a good understanding of UX aesthetics gained from working with Power BI, Tableau or other data visualisation platforms for client facing deliverables
- Working with large and complex datasets, ideally in structured databases and distributed systems like Databricks
- Cloud-based platforms such as Microsoft Azure, AWS or Google Cloud
- Generative AI and machine learning concepts and applications
- Structured and unstructured data management
- Statistical analysis and predictive modelling
- AI-enabled analytics and automation solutions
Qualifications Qualification in a Highly Numerate Subject (e. g.
Computer Science, Operational Research, Statistics, Mathematics, Engineering, or Economics) or equivalent experience Ideally, You'll Also Have
- Experience of financial, operational, and commercial reporting and relevant performance metrics
- An understanding of basic corporate finance and accounting concepts
- Experience of working in a professional services environment, including exposure to high profile transactions
- Knowledge and experience relating to one or more specific sectors is preferred
- Experience of working with visualisation tools including Power BI, Tableau, Tibco Spotfire, RShiny, plotly-dash, D3. js, or Qlik Sense
- Experience in SQL (any variant), MS Excel and VBA
- Experience in applying various analytical techniques (e. g. naïve bayes, decision trees, random forest, xgboost and k-means), to calculate problems such as predictive forecasting, prescriptive action, capacity planning.
- Experience of working in teams, managing the workload of junior team members, and coaching junior staff
- Interest in emerging AI technologies and their application in solving business challenges
- Experience working within cross-functional teams and managing multiple stakeholders
- What We Look For
- Individuals who are passionate about using data and AI to solve critical business problems
- Strong communicators who can bridge the gap between business stakeholders and technical teams
- Professionals who combine analytical rigour with commercial thinking
- Team players who thrive in collaborative environments and contribute positively to team culture
- Individuals who are adaptable and excited by the rapidly evolving analytics and AI landscape
- EY | Building a better working world
- #J-18808-Ljbffr
Manager, Analytics & AI, EY-Parthenon employer: Ernst & Young
EY is an exceptional employer, offering a dynamic and inclusive work culture that prioritises employee growth and development. With a commitment to flexible working arrangements and a comprehensive Total Rewards package, employees can tailor their benefits to suit their needs while contributing to cutting-edge cyber security solutions in a rapidly expanding global practice. Join us in London, Manchester, or Scotland, and be part of a team that values collaboration, innovation, and making a meaningful impact in the world of cyber security.
StudySmarter Expert Advice🤫
We think this is how you could land Manager, Analytics & AI, EY-Parthenon
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We think you need these skills to ace Manager, Analytics & AI, EY-Parthenon
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Ernst & Young, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Ernst & Young. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Ernst & Young
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Ernst & Young!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
