Data and Analytics -Pricing and Commercial - Senior
Data and Analytics -Pricing and Commercial - Senior
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Job Description
At EY youll have the chance to build a career as unique as you are with the global scale support inclusive culture and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better too. Join us and build an exceptional experience for yourself and a better working world for all.
Job Description (Shaded areas for Talent use only)
We are seeking a passionate data analyst to transform data into actionable insights and support decision-making in a global organization focused on pricing and commercial strategy. This role spans business analysis requirements gathering data modeling solution design and visualization using modern tools. The analyst will also maintain and improve existing analytics solutions interpret complex datasets and communicate findings clearly to both technical and non-technical audiences.
Essential Functions of the Job:
- (Identify and describe essential functions or primary duties and responsibilities. Each function should describe WHAT is done and the END RESULT/PURPOSE achieved. Assume that the reader does not know the role or function of the job.)
- Analyze and interpret structured and unstructured data using statistical and quantitative methods to generate actionable insights and ongoing reports.
- Design and implement data pipelines and processes for data cleaning transformation modeling and visualization using tools such as Power BI SQL and Python.
- Collaborate with stakeholders to define requirments prioritize business needs and translate problems into analytical solutions.
- Develop maintain and enhance scalable analytics solutions and dashboards that support pricing strategy and commercial decision-making.
- Identify opportunities for process improvement and opperational efficiency through data-driven recommendations.
- Communicate complex findings in a clear compelling and actionable manner to both technical and non-technical audiences.
Analytical/Decision Making Responsibilities:
- (Describe the kind of problems and challenges typically faced and decisions required to perform the job as well as recommendations made to supervisors or others. Focus on the nature of existing policies precedents and procedures used to guide decisions and the degree to which the incumbent is free to make decisions requiring interpretation and judgment. Provide an example.)
- Apply a hypothesis-driven approach to analyzing ambiguous or complex data and synthesizing insights to guide strategic decisions.
- Promote adoption of best practices in data analysis modeling and visualization while tailoring approaches to meet the unique needs of each project.
- Tackle analytical challenges with creativity and rigor balancing innovative thinking with practical problem-solving across varied business domains.
- Prioritize work based on business impact and deliver timely high-quality results in fast-paced environments with evolving business needs.
- Demonstrate sound judgement in selecting methods tools and data sources to support business objectives.
Knowledge and Skills Requirements:
- (Describe the knowledge or skills needed to perform this job; these may be professional technical or managerial)
- Proven experience as a data analyst business analyst data engineer or similar role.
- Strong analytical skills with the ability to collect organize analyze and present large datasets accurately.
- Foundational knowledge of statistics including concepts like distributions variance and correlation.
- Skilled in documenting processes and presenting findings to both technical and non-technical audiences.
- Hands-on experience with Power BI for designing developing and maintaining analytics solutions.
- Proficient in both Python and SQL with strong programming and scripting skills.
- Skilled in using Pandas T-SQL and Power Query M for querying transforming and cleaning data.
- Hands-on experience in data modeling for both transactional (OLTP) and analytical (OLAP) database systems.
- Strong visualization skills using Power BI and Python libraries such as Matplotlib and Seaborn.
- Experience with defining and designing KPIs and aligning data insights with business goals.
Additional/Optional Knowledge and Skills:
- (Describe any additional knowledge or skills that while not required may be useful or helpful to perform this job; these may be professional technical or managerial)
- Experience with the Microsoft Fabric data analytics environment.
- Proficiency in using the Apache Spark distributed analytics engine particularly via PySpark and Spark SQL.
- Exposure to implementing machine learning or AI solutions in a business context.
- Familiarity with Python machine learning libraries such as scikit-learn XGBoost PyTorch or transformers.
- Experience with Power Platform tools (Power Apps Power Automate Dataverse Copilot Studio AI Builder).
- Knowledge of pricing commercial strategy or competitive intelligence.
- Experience with cloud-based data services particularly in the Azure ecosystem (e.g. Azure Synapse Analytics or Azure Machine Learning).
Supervision Responsibilities:
- (Describe the level of supervision received i.e. the frequency of supervisory contact degree to which the individual acts independently and on what kinds of issues. Describe the level of supervision of others if any i.e. assigning work reviewing performance direct or indirect responsibility).
- Operates with a high degree of independence and autonomy.
- Collaborates closesly with cross-functional teams including sales pricing and commercial strategy.
- Mentors junior team members helping develop technical skills and business domain knowledge.
Other Requirements:
- (Describe any miscellaneous functions or expectations of the job that are important to note)
- Collaborates with a team operating primarily in the Eastern Time Zone (UTC 4:00 / 5:00).
- Limited travel may be required for this role.
Job Requirements:
Education:
- (What is the minimum level of education or equivalent experience needed/suggested to perform this job effectively)
- A bachelors degree in a STEM field relevant to data analysis data engineering or data science is required. Examples include (but are not limited to) computer science statistics data analytics artificial intelligence operations research or econometrics.
Experience:
- (What is the minimum number or range of years needed to perform this job)
- 36 years of experience in data analysis data engineering or a closely related field ideally within a professional services enviornment.
Certification Requirements:
(Describe and explain any certifications and/or licenses needed or helpful to perform this job).
- No certifications are required for this role.
EY Building a better working world
EY exists to build a better working world helping to create long-term value for clients people and society and build trust in the capital markets.
Enabled by data and technology diverse EY teams in over 150 countries provide trust through assurance and help clients grow transform and operate.
Working across assurance consulting law strategy tax and transactions EY teams ask better questions to find new answers for the complex issues facing our world today.
Employment Type
Full Time
