Halo Insurance Data Science Senior Associate
- Experience 0-5 Years
- Category Assurance
- Location New York, NY
PwC is a network of firms committed to delivering quality in assurance, tax and advisory services.
We help resolve complex issues for our clients and identify opportunities. Learn more about us at www.pwc.com/us.
At PwC, we develop leaders at all levels. The distinctive leadership framework we call the PwC Professional (http://pwc.to/pwcpro) provides our people with a road map to grow their skills and build their careers. Our approach to ongoing development shapes employees into leaders, no matter the role or job title.
Are you ready to build a career in a rapidly changing world? Developing as a PwC Professional means that you will be ready
- to create and capture opportunities to advance your career and fulfill your potential. To learn more, visit us at www.pwc.com/careers.
What will you do if you work in Assurance at PwC?
You'll ask questions and test assumptions. You'll help determine if companies are reporting information that investors and others can rely on. You'll help businesses solve complex issues faced by management and boards. You'll serve the public interest and the capital markets by conducting quality audits. Visit http://pwc.to/pwcassurance for more information on PwC's Assurance practice.
The world is quickly changing, that's why PwC is quickly adapting. We're capitalizing on trends that will impact corporate reporting.
Our focus is on globalization, technology, sustainability and environmental reporting, population shifts and regulation. We combine skills and experience to help our clients address their challenges.
Boards of Directors and executive management recognize the ever increasing importance of effective risk management efforts in meeting their organization's strategic objectives.
PwC's Risk Assurance practice has developed a holistic approach to risk that protects businesses, facilitates strategic decision making and enhances efficiency. Our holistic approach is complimented by the extensive risk and controls technical knowledge and sector-specific experience our Risk Assurance professionals possess.
The end result is a risk solution that is tailored to meet the unique needs of a company.
Areas where our Risk Assurance practice can bring value to an organization include:
- Leveraging industry and technical expertise to assist management to address more effectively risks associated with their business
- Assisting management in the assessment of project risks and controls
- Enhancing internal audit functions to further align to company strategy and risk
- Reducing company costs through strategic internal audit outsourcing and co-sourcing solutions
- Increasing value and reducing costs of compliance-related activities
- Identifying opportunities for companies to effectively mitigate risk and improve business performance
- Applying the concepts of Enterprise Risk Management to help companies identify, assess, mitigate and proactively consider emerging risks
Data Analytics Transformation focuses on services related to data auditing, business analytics, visualization and leveraging of analytic technologies to evaluate complex Enterprise Systems, such as SAP, EBS, PeopleSoft and JD Edwards, for audit and non-audit services.
The team provides a range of solutions including:
- Design and build automated tests to automate and support the delivery of audit and non-audit services;
- Evaluate ERP data models, data flows and system functionality;
- Document functional and technical specifications;
- Coding of the automated test scripts;
- Generate output per business requirements, such as tailored Excel reporting or visualizations; and,
- Development of an analytic application, web portal and underlying infrastructure to enable the delivery of the automated tests, including ETL, analytics engine, reporting engine and end-user portals.
Data Science is a field where practitioners help build analytical content to support PwC assurance professionals discover and explain risk to their clients.
Various analytical products are utilized to code and implement multiple factor predicted outcomes into key risk measures, identify unusual activity through machine learning, or extend sample-based testing to massive enterprise-wide data stores. Real-world questions and real-world data present unexpected challenges and at PwC you will learn how to apply theory to practice working with our close-knit team.
Minimum Year(s) of Experience: 2 years of relative work experience
Minimum Degree Required: Bachelor's degree in Accounting, Finance/Economics, Management Information Systems, Computer Science, Business Administration, Statistics Mathematics, Regulatory Compliance, Science, Technology, Engineering and Mathematics and/or other business fields of study.
Degree Preferred: Master's degree or Doctorate Double major, or major and minor, combining a technical focus
- Engineering / Mathematics / Statistics / Computer Science
- with a professional serves oriented focus
- Business / Economics.
Demonstrates thorough knowledge of and/or proven record of success in data analytics, preferably for a global network of professional services firms, in one or more of the following areas:
- Participation in planning with other data scientists on the most effective analytical approach based upon requirements taking into consideration performance and scalability to large datasets;
- Designing and building analytical procedures;
- Performing unit and system testing to validate the output of the analytic procedures against expected results;
- Generating reporting output for leadership;
- Understanding of relational databases and SQL; NoSQL database models, XML and other database models; development languages, such as Python, C#, Java or equivalent and applying analytical methods to large datasets leveraging one of those languages;
- Utilization of ETL tools and techniques, such as Informatica, SSIS, Mapforce to map transformation and flow of data from a source to a target system;
- Demonstrates some knowledge in an applied subject matter such as finance, accounting, energy, or health care; and,
- Demonstrates basic knowledge in engineering custom analytical approaches to unique or challenging questions when standard approaches fall short.
Demonstrates thorough level of ability and/or proven record of success in the application of statistical or numerical methods, data munging or data-driven problem solving, preferably for a global network of professional services firms, with emphasis on the following areas:
- Utilizing techniques such as multivariate regressions, Bayesian probabilities, clustering algorithms, machine learning, dynamic programming, stochastic-processes, queueing theory, algorithmic knowledge to efficiently research and solve complex development problems and application of engineering methods to define, predict and evaluate the results obtained;
- Developing solutions through SQL development, data analytics and programming/scripting utilizing Python, Java, C#, C++, Python, .NET, VB, etc.;
- Applying moderately complex mathematical or statistical methodologies; and,