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Senior Associate, Data Scientist (Non-Financial Risk)

KPMG Advisory practice is currently our fastest growing practice. We are seeing tremendous client demand, and looking forward we do not anticipate that slowing down. In this ever-changing market environment, our professionals must be adaptable and thrive in a collaborative, team-driven culture. At KPMG, our people are our number one priority. With a wealth of learning and career development opportunities, a world-class training facility and leading market tools, we make sure our people continue to grow both professionally and personally. If you're looking for a firm with a strong team connection where you can be your whole self, have an impact, advance your skills, deepen your experiences, and have the flexibility and access to constantly find new areas of inspiration and expand your capabilities, then consider a career in Advisory.KPMG is currently seeking a Senior Associate, NFR Data Science in Non-Financial Risk for our Consulting practice.Responsibilities:• Serve as a technical resource on projects to design and develop advanced AI/ML solutions to meet clients' unique requirements, including participation in internal and external discussions to gather business use case requirements, provide advanced analytics and data science expertise and solution options for business problems• Engineer solutions using natural language processing and machine learning techniques to solve critical problems and improve processes for clients across capital markets and financial services businesses, including trade surveillance, electronic communications surveillance, payments fraud detection, third-party risk management and other operational risk categories• Utilize machine learning, natural language, and statistical analysis methods, such as sentiment analysis, topic modeling, time-series analysis, regression, classification, statistical inference, and validation methods to review financial services client risks• Perform explanatory data analyses, generate and test working hypotheses, prepare and analyze historical data and identify patterns to develop innovative solutions to financial services operational risk and regulatory compliance programs• Mentor junior data scientists and help to grow data science expertise within the broader team, including offshore• Collaborate with diverse, cross-functional teams to accurately identify and prioritize requirements, helping to ensure that AI/ML solutions meet the needs and expectations of various stakeholdersQualifications:• Minimum three years of recent professional experience working in advanced analytics and data science• Bachelor's degree from an accredited college/university in a relevant STEM field such as data science, computer science, engineering, mathematics, physics and other related fields• Extensive experience in AI/ML algorithm development and data analysis including at least one of the following: NLP, time-series analysis, predictive modeling• Experience in a statistical programming language (for example, R or Python) and related data science / machine learning packages (for example, Pandas, Scikit-learn, Pytorch, Transformers); experience with scripting, data structures and algorithms and ability to work with large amounts of data• Excellent communication, written, presentation, and problem-solving skills• Previous technical client service experience preferred• Must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa) and have the ability to travel regularlyKPMG complies with all local/state regulations regarding displaying salary ranges. If required, the ranges displayed below or via the URL below are specifically for those potential hires who will work in the location(s) listed. Any offered salary is determined based on relevant factors such as applicant's skills, job responsibilities, prior relevant experience, certain degrees and certifications and market considerations. In addition, the firm is proud to offer a comprehensive, competitive benefits package, with options designed to help you make the best decisions for yourself, your family, and your lifestyle. Available benefits are based on eligibility. Our Total Rewards package includes a variety of medical and dental plans, vision coverage, disability and life insurance, 401(k) plans, and a robust suite of personal well-being benefits to support your mental health. Depending on job classification, standard work hours, and years of service, KPMG provides Personal Time Off per fiscal year. Additionally, each year the firm publishes a calendar of holidays to be observed during the year and provides two firmwide breaks each year where employees will not be required to use Personal Time Off; one is at year end and the other is around the July 4th holiday. Additional details about our benefits can be found towards the bottom of our KPMG US Careers site at “Benefits & How We Work”.Follow this link to obtain salary ranges by city outside of CA:https://kpmg.com/us/en/how-we-work/pay-transparency.html/?id=M116_4_25KPMG LLP (the U.S. member firm of KPMG International) offers a comprehensive compensation and benefits package. KPMG is an equal opportunity employer. KPMG complies with all applicable federal, state and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, protected veteran status, or any other category protected by applicable federal, state or local laws. The attached link contains further information regarding the firm's compliance with federal, state and local recruitment and hiring laws. No phone calls or agencies please.KPMG does not currently require partners or employees to be fully vaccinated or test negative for COVID-19 in order to go to KPMG offices, client sites or KPMG events, except when mandated by federal, state or local law. In some circumstances, clients also may require proof of vaccination or testing (e.g., to go to the client site).KPMG recruits on a rolling basis. Candidates are considered as they apply, until the opportunity is filled. Candidates are encouraged to apply expeditiously to any role(s) for which they are qualified that is also of interest to them.Los Angeles County applicants: Material job duties for this position are listed above. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, and safeguard business operations and company reputation. Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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What You Should Know About Senior Associate, Data Scientist (Non-Financial Risk), KPMG

Are you ready to take on the exciting role of Senior Associate, Data Scientist (Non-Financial Risk) at KPMG in Short Hills, NJ? At KPMG, we're experiencing a tremendous surge in client demand within our Advisory practice, and we're looking for adaptable team players to join us! This isn't just a position; it’s an opportunity to participate in crafting advanced AI and machine learning solutions that address unique client needs in a dynamic marketplace. As part of our Collaborative culture, you will serve as a vital technical resource, utilizing your expertise to engineer solutions that tackle challenges such as trade surveillance and fraud detection. You will engage in both internal and external discussions to gather requirements while mentoring junior data scientists to enhance our team's capabilities. With at least three years in advanced analytics and machine learning, you'll bring extensive experience in AI/ML algorithm development and statistical analysis. A Bachelor's degree in a STEM field is a must, alongside proficiency in R or Python and knowledge of data science packages like Scikit-learn and Pandas. Joining KPMG means being part of a firm that values personal growth and work-life balance while providing a comprehensive benefits package tailored to support your lifestyle. If you're looking to make a meaningful impact in the world of Non-Financial Risk, we’d love to meet you!

Frequently Asked Questions (FAQs) for Senior Associate, Data Scientist (Non-Financial Risk) Role at KPMG
What are the responsibilities of a Senior Associate, Data Scientist (Non-Financial Risk) at KPMG?

As a Senior Associate, Data Scientist (Non-Financial Risk) at KPMG, you'll be responsible for designing and developing advanced AI and machine learning solutions tailored to clients' needs. This includes gathering business use case requirements, utilizing natural language processing techniques, conducting statistical analyses, and mentoring junior data scientists. Your role will often involve collaboration with cross-functional teams to ensure our AI/ML solutions meet stakeholder expectations.

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What qualifications are required for the Senior Associate, Data Scientist position at KPMG?

To be considered for the Senior Associate, Data Scientist (Non-Financial Risk) role at KPMG, candidates should hold a Bachelor's degree in a relevant STEM field and have at least three years of professional experience in advanced analytics and data science. Proficiency in statistical programming languages like R or Python and experience with AI/ML algorithm development are essential, along with strong communication and problem-solving skills.

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How does KPMG support personal and professional development for data scientists?

KPMG places a high value on personal and professional development. As a Senior Associate, Data Scientist (Non-Financial Risk), you will have access to a world-class training facility, numerous learning opportunities, and a collaborative environment designed to foster your growth. We encourage continual learning and advancement through mentorship, advanced projects, and participation in cutting-edge technology initiatives.

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What types of projects will a Senior Associate, Data Scientist work on at KPMG?

In the role of Senior Associate, Data Scientist (Non-Financial Risk) at KPMG, you will work on a variety of projects that focus on critical operational risks in financial services. These projects may include developing machine learning models for fraud detection, optimizing trade surveillance processes, or improving third-party risk management protocols, all aimed at enhancing regulatory compliance and client satisfaction.

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What benefits does KPMG offer to its Senior Associate, Data Scientist employees?

KPMG offers a comprehensive benefits package for its employees, including options for medical and dental coverage, vision insurance, life and disability insurance, and a robust 401(k) plan. Additionally, employees enjoy ample time-off benefits, well-being options, and flexible working structures that promote a healthy work-life balance, making KPMG a supportive and enriching workplace.

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Common Interview Questions for Senior Associate, Data Scientist (Non-Financial Risk)
Can you describe your experience with machine learning algorithms?

When answering this question, focus on specific algorithms you've worked with, mentioning projects where you applied them. Highlight your understanding of how these algorithms fit within broader data science frameworks and the impact they had on business outcomes. If possible, provide quantitative evidence of their effectiveness.

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How do you approach problem-solving within data science?

In your response, demonstrate a systematic approach to problem-solving that includes defining the problem, analyzing data, generating hypotheses, testing solutions, and iterating. Provide examples of specific challenges you’ve faced in past roles and how your methods led to successful outcomes.

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What statistical programming languages are you proficient in, and how have you used them?

Be prepared to discuss your proficiency in languages like R or Python, mentioning specific libraries you've used, like Scikit-learn or Pandas. Provide examples of projects where these languages were crucial for data manipulation and analysis, illustrating your coding competency.

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What techniques do you use for data visualization?

Highlight your experience with data visualization tools and techniques, explaining how you choose the right method for different types of data. Give examples of how effective visualizations you've created have communicated insights to stakeholders, aiding decision-making processes.

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How do you stay current with developments in AI and machine learning?

Talk about your methods for keeping up-to-date, such as following industry publications, attending conferences, or engaging in online courses. Emphasize how this continuous learning directly impacts your work and enhances your contributions to the team.

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Can you give an example of a successful collaboration in a cross-functional team?

Provide a specific example where your collaboration efforts resulted in a successful project. Focus on how you navigated challenges, ensured clear communication, and leveraged team members' strengths to reach a common goal.

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What experience do you have in mentoring junior staff?

Discuss your approach to mentorship, including how you provide support and share knowledge with junior team members. Share examples of how you've guided their development and contributed to their professional growth.

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How do you handle tight deadlines in your work?

Explore your time management strategies, such as prioritizing tasks and breaking projects into manageable steps. Share examples of how you’ve met deadlines while maintaining high quality in your deliverables.

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What challenges have you faced in data science, and how did you overcome them?

Be honest about challenges you’ve encountered, providing examples that demonstrate your problem-solving and adaptability. Highlight the lessons learned and how these experiences have made you a stronger data scientist.

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Why do you want to work at KPMG as a Senior Associate, Data Scientist?

Share your motivations for applying to KPMG, emphasizing the firm's commitment to innovation, team collaboration, and professional growth. Align your career goals with the opportunities you see at KPMG, showcasing your enthusiasm for contributing to their success in the Non-Financial Risk sphere.

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KPMG is one of the world’s leading professional services firms and the fastest growing Big Four accounting firm in the United States. With 75+ offices and more than 40,000 employees and partners through out the U.S., we’re leading the industry in ...

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