Manager, Machine Learning Modeler

Kpmg Washington , DC 20319

Posted 6 days ago

Innovate. Collaborate. Shine. Digital Lighthouse houses KPMG's specialized capabilities across the digital landscape: applied data science, AI, data engineering and insights, software engineering, automation, and big data. Here, you'll work with a sophisticated team of professionals to explore solutions for clients in a multiplatform environment. This means your ability to find answers is limited only by your creativity in leveraging a vast array of techniques and tools. Be a part of a high-energy, unique, fast-paced, and innovative culture that delivers with the agility of a tech startup and the backing of a leading global consulting firm. In this particular role, you'll work specifically in the AI Analytics & Engineering Community within the Digital Lighthouse, on a wide range of projects. From applied AI to optimization to big data platform engineering, your analytical and technical skills will drive real impact in the business world. So, bring your ingenuity and pioneering spirit to KPMG Digital Lighthouse.

KPMG is currently seeking a Manager Machine Learning Modeler to join our KPMG Lighthouse - Center of Excellence for Advanced Analytics.

Responsibilities:

  • Lead multi-disciplinary and cross-functional teams to identify business opportunities and define artificial intelligence solutions; Utilize processes and best practices to plan, lead, and execute delivery of artificial intelligence engagements, and work with clients to manage risks, set expectations and ensure successful delivery across different areas (technology, financial services, emerging tech, government agencies federal, state and local, and utilities)

  • Deliver client project modeling work stream through direct ownership of data integration, validation, mining, and quantitative modeling deliverables; Lead project delivery by tracking and communicating project risks, budget, rates, and launch/closeout activities, including the administration of work papers and collaboration sites

  • Assess, capture and translate issues and requirements into structured analytics use case, including rapid learning of industry/domain/client dynamics and development of effective work stream plans

  • Work with clients to discover data sources, and create data requests; Lead the ETL process to ingest and enrich structured and unstructured data; Leverage a variety of data sources such as social media, news, internal/external documents, images, video, voice, emails, financial data and operational data

  • Plan engagement objectives and key deliverables; manage using analytics processes to mitigate risks in data, modeling, validation and delivery; Work with team members to capture assumptions, and risks, and develop approaches to mitigate issues; Deliver on engagement milestones by following analytics processes to mitigate risks in data, modeling, validation and delivery; manage assumptions, risks, and work with others to clear issues

  • Proactively broaden and deepen client relationships by working with varying levels of client team members

Qualifications:

  • Minimum five years of experience involving modeling (regression, machine learning, feature selection, dimension, reduction, validation); Data (extracting, preparing, munging, validating); Building analytics pipelines, data science landscape and software development lifecycle; Two years of training specific to artificial intelligence, and five years of experience leading teams of five or more data scientists, engineers and other data & analytics professionals

  • Bachelor's degree or Master's degree from an accredited college/university in a quantitative discipline, such as Data Science, Analytics, Computer Science, Engineering, or Mathematics

  • Strong knowledge in delivering analytics projects using leading processes including skilled knowledge of data discovery, cleaning, model selection, validation, and deployment; designing and building of machine learning pipelines (data extraction, feature engineering from structured and unstructured data)

  • Ability to apply artificial intelligence techniques to achieve concrete business goals; ability to work with the business to understand available resources and constraints around data (sources, integrity, and definitions), processing platforms, and security; Provide assistance and resolve problems, using solid problem-solving skills with strong verbal/written communication skills

  • Proficiency with sophisticated analytics tools and programming languages such as SAS, R, Python, Java, Spark, Hadoop, Alteryx and SQL; Data visualization tools such as Tableau and QlikView

  • 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 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, sex, sexual orientation, gender identity, national origin, 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.


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Manager, Machine Learning Modeler

Kpmg