Assurance Data Scientist (Senior Manager)
Ernst & Young Global Limited
Johannesburg, Gauteng, South Africa
5d ago

JOB DESCRIPTION The Data Scientist role is responsible for modelling complex problems, discovering insights and identifying process digital improvements or opportunities through the use of statistical, algorithmic, mining and visualization techniques.

In addition to advanced analytic skills, this role is also proficient at integrating and preparing large, varied datasets, architecting specialized database and computing environments, and communicating results.

Data Scientists work closely with clients, data stewards, project / program managers, and other IT teams to turn data into critical information and knowledge that can be used to make sound organizational decisions.

Other responsibilities include providing data that is congruent and reliable. Need to be creative thinkers and propose innovative ways to look at problems by using data mining (the process of discovering new patterns from large datasets) approaches on the set of information available.

Need to validate the findings using an experimental and iterative approach. Will also need to be able to present back the findings to the business by exposing the assumptions and validation work in a way that can be easily understood by the business counterparts.

The Data Scientist will need a combination of business focus, strong analytical and problem solving skills and programming knowledge to be able to quickly cycle hypothesis through the discovery phase of the project.

Excellent written and communications skills to report back the findings in a clear, structured manner are required. Work Complexity

  • Designs experiments, test hypotheses, and build models.
  • Conducts advanced data analysis and highly complex designs algorithm.
  • Applies advanced statistical and predictive modelling techniques to build, maintain, and improve on multiple real-time decision systems.
  • Responsibilities 1. Business Requirements

  • Leads discovery processes with stakeholders to identify the business requirements and the expected outcome.
  • Works with and alongside business analysts by suggesting other products of interest to the client.
  • Models and frames business scenarios that are meaningful and which impact on critical business processes and / or decisions.
  • 2. Data Requirements and Architecture

  • Identifies what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as smart meters and geo-location information or social media.
  • Collaborates with subject matter experts to select the relevant sources of information.
  • Makes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices.
  • 3. Analysis

  • Develops innovative and effective approaches to solve client's analytics problems and communicates results and methodologies.
  • Works in iterative processes with the client and validates findings.
  • Develops experimental design approaches to validate finding or test hypotheses.
  • Validates analysis using scenario modelling.
  • Identifies / creates the appropriate algorithm to discover patterns.
  • 4. Qualification and Assurance

  • Assesses, with the business, opportunities to enhance the qualification and assurance of the information to strengthen the use case.
  • Defines the validity of the information, how long the information is meaningful, and what other information it is related to.
  • 5. Access Management and Control

  • Works with the data steward to ensure that the information used in compliance with the regulatory and security policies in place.
  • Qualifies where information can stored or what information, external to the organization, may be used support of the use case.
  • 6. QuantificationUtilizes patterns and variations in the volume, speed and other characteristics of data supporting the initiative, the type of data (e.

    g., images, text, clickstream or metering data) in predictive analysis. 7. Policies, Standards and Procedures

  • Develops usage and access control policies and systems in collaboration with the data steward.
  • Partners with the data stewards in continuous improvement processes impacting data quality in the context of the specific use case.
  • Recommends ongoing improvements to methods and algorithms that lead to findings including new information.
  • 8. Communications / Presentations

  • Presents and depicts the rationale of their findings in easy to understand terms for the business.
  • Presents back results that contradict common belief, if needed.
  • Communicates and works with business subject matter experts and organizational leadership.
  • 9. Change Advocacy

  • Educates the organization both from IT and the business perspectives on new approaches, such as testing hypotheses and statistical validation of results.
  • Helps the organization understand the principles and the math behind the process to drive organizational buy-in.
  • 10. Metrics

  • Provides business metrics for the overall project to show improvements (contribution to the improvement should be monitored initially and over multiple iterations).
  • Demonstrates the following scientist qualities : clarity, accuracy, precision, relevance depth, breadth, logic, significance, and fairness.
  • 11. PerformanceProvides on-going tracking and monitoring of performance of decision systems and statistical models. 12. SupportLeads the design and deployment of enhancements and fixes to systems as needed.

    Competencies 1. Change Advocate : Identifies and acts upon opportunities for continuous improvement. Encourages prudent risk-taking, exploration of alternative approaches, and organizational learning.

    Demonstrates personal commitment to change through actions and words. Mobilizes others to support change through times of stress and uncertainty.

    2. Communications for Results : Expresses technical and business concepts, ideas, feelings, opinions, and conclusions orally and in writing.

    Listens attentively and reinforces words through empathetic body language and tone. 3. Conceptual Thinking : Synthesizes facts, theories, trends, inferences, and key issues and / or themes in complex and variable situations.

    Recognizes abstract patterns and relationships between apparently unrelated entities or situations. Applies appropriate concepts and theories in the development of principles, practices, techniques, tools and solutions.

    4. Information Seeking : Gathers and analyses information or data on current and future trends of best practice. Seeks information on issues impacting the progress of organizational and process issues.

    Translates up to date information into continuous improvement activities that enhance performance.5. Innovation : Improves organizational performance though the application of emerging technologies, methods, processes, products and services.

    Employs sound innovations will be deployed to produce return on investment.6. Problem Solving : Anticipates, identifies and defines problems.

    Seeks root causes. Develops and implements practical and timely solutions. 7. Teamwork : Collaborates with other members of formal and informal groups in the pursuit of common missions, vision, values and mutual goals.

    Places team needs and priorities above personal needs. Involves others in making decisions that affect them. Draws on the strengths of colleagues and gives credit to others' contributions and achievements.

    Education or Experience Required

  • Bachelors in mathematics, statistics, engineering or computer science or related field; Masters or PHD degree preferred.
  • 5 or more years of relevant quantitative and qualitative research and analytics experience.
  • Solid knowledge of statistical techniques as well as information and data architecture.
  • Ability to come up with solutions to loosely defined business problems by leveraging pattern
  • Detection over potentially large datasets.
  • Strong programming skills (such as Hadoop MapReduce or other big data frameworks, Java),
  • Statistical modelling (like SAS or R).
  • Experience using machine learning algorithms.
  • High proficiency in the use of statistical packages.
  • Proficiency in statistical analysis, quantitative analytics, forecasting / predictive analytics, multivariate testing, and optimization algorithms.
  • Strong communication and interpersonal skills.
  • Experience leading teams.
  • In-depth industry / business knowledge.
  • Who we are : At EY we support you in achieving your unique potential both personally and professionally. We give you stretching and rewarding experiences that keep you motivated, working in an atmosphere of integrity and teaming with some of the world's most successful companies.

    And while we encourage you to take personal responsibility for your career, we support you in your professional development in every way we can.

    You enjoy the flexibility to devote time to what matters to you, in your business and personal lives. At EY you can be who you are and express your point of view, energy and enthusiasm, wherever you are in the world.

    It's how you make a difference. Please note : Preference will be given to PDI candidates.

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