Sr. Associate, Data Scientist

at  KPMG

We are The Lighthouse within KPMG’s Consulting practice. We tap into the power of emerging technologies and scientific breakthroughs to create solutions and products that address the largest and most complex issues faced by global companies. By blending technology with our industry expertise, we’re able to harness the potential of Cloud, AI, ML, IoT, 5G, and quantum computing to design and implement real-world solutions for a variety of business problems. Work with confidence knowing your ideas are heard and backed by one of the world’s top professional services firms. Spark your curiosity and ignite your career at The Lighthouse.
KPMG is currently seeking a Sr. Associate to join our KPMG Lighthouse - Center of Excellence for Advanced Analytics.

Responsibilities:

• Develop code to prepare, extract, and enrich a variety of structured and unstructured data sources, working with the business to understand available resources and constraints around data. Perform exploratory data analysis, generate and test working hypotheses, and uncover interesting trends and relationships.
• Build and implement machine learning algorithms to analyze and model structured or unstructured data. Understand benefits of different approaches to decide on tools, features, and methodology for the business problem. Leverage detailed knowledge of advanced statistical and mathematical methods from statistics, machine learning, data mining, econometrics, and operations research.
• Communicate technical details of solution, including mathematical formulations, alternatives, and impact on modeling approach to business stakeholders across industries (technology, financial services, emerging tech, government agencies - federal, state and local, and utilities).
• Create production quality data pipelines and ML pipelines that can be deployed at scale. Make use of in-house platforms in solution development, and recommend and develop new capabilities.
• Translate advanced business analytics problems into technical approaches that yield actionable recommendations, in diverse domains (risk management, product development, marketing research, supply chain, and public policy). Identify trends, patterns, and insights for data-driven decision making.
• Work in multi-disciplinary and cross-functional teams to rapidly iterate models and results to refine and validate approach; Work in a fast-paced and dynamic environment with both virtual and face-to-face interactions; Utilize structured approaches to solving problems, managing risks, and documenting assumptions while communicating results and educating others through insightful visualizations, reports, and presentations.

Qualifications:

• Minimum of two years of experience leading work streams with at least two data scientists, engineers, and other data & analytics professionals, including innovation, quality management, utilizing analytics and software development processes for natural language processing, machine learning on unstructured data, and/or information retrieval; Multidisciplinary backgrounds.
• Master’s Degree from an accredited college/university in Computer Science, Statistics, Data Science, Engineering, or related fields. PhD from an accredited college/university is preferred.
• Excellent problem-solving skills, verbal/written communication, and ability to explain technically complex concepts to business stakeholders.
• Deep technical understanding of data preparation approaches and machine learning algorithms. Solid experience performing data science from data discovery, cleaning, model selection, validation, to deployment.
• Experience coding artificial intelligence methods using object-oriented programming in a software development process, and ability to restructure, refactor, and optimize code for efficiency.
• Ability to utilize a diverse array of technologies and tools as needed, to deliver insights, such as fluency in Python or R; Experience with SQL and cloud technology preferred; Experience with command-line scripting, data structures, and algorithms; Ability to work in Linux and/or cloud environments; Ability to write production level code.
• Ability to travel up to eighty percent of the time; Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

KPMG 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=M150A424KPMG LLP (the U.S. member firm of KPMG International) offers a comprehensive compensation and benefits package. KPMG is an affirmative action-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 “https://assets.kpmg.com/content/dam/kpmg/us/pdf/2018/09/eeo.pdf? ”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

• Develop code to prepare, extract, and enrich a variety of structured and unstructured data sources, working with the business to understand available resources and constraints around data. Perform exploratory data analysis, generate and test working hypotheses, and uncover interesting trends and relationships.
• Build and implement machine learning algorithms to analyze and model structured or unstructured data. Understand benefits of different approaches to decide on tools, features, and methodology for the business problem. Leverage detailed knowledge of advanced statistical and mathematical methods from statistics, machine learning, data mining, econometrics, and operations research.
• Communicate technical details of solution, including mathematical formulations, alternatives, and impact on modeling approach to business stakeholders across industries (technology, financial services, emerging tech, government agencies - federal, state and local, and utilities).
• Create production quality data pipelines and ML pipelines that can be deployed at scale. Make use of in-house platforms in solution development, and recommend and develop new capabilities.
• Translate advanced business analytics problems into technical approaches that yield actionable recommendations, in diverse domains (risk management, product development, marketing research, supply chain, and public policy). Identify trends, patterns, and insights for data-driven decision making.
• Work in multi-disciplinary and cross-functional teams to rapidly iterate models and results to refine and validate approach; Work in a fast-paced and dynamic environment with both virtual and face-to-face interactions; Utilize structured approaches to solving problems, managing risks, and documenting assumptions while communicating results and educating others through insightful visualizations, reports, and presentations