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The opportunity
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 option