Associate Data Scientist - ML Pipelines for AI 2020 National

Responsibilities & Qualifications

KPMG is currently seeking an Associate for our Lighthouse - Data & Analytics Data Science Machine Learning Pipelines for AI practice.

While this requisition may state a specific geographic office, please note that our positions are location flexible between our major hubs. Opportunities may include, but are not limited to, Atlanta, Chicago, Dallas, Denver, New York City, Orange County, Philadelphia, Seattle, Washington DC. Please proceed with applying here, and let us know your location preference during interview phase if applicable.

Responsibilities:

• Work in multi-disciplinary and cross-functional client-facing KPMG teams to translate business requirements into artificial intelligence goals and modeling approaches; rapidly iterate models and results to refine and validate approach. 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).

• Participate 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.

• Deliver on engagement milestones by following analytics processes for data, modeling, validation, and delivery; manage assumptions, and risks, and work with others to clear issues.

• Build production-ready machine learning-enabled systems and data ingestion processes to prepare, extract, and enrich a variety of structured and unstructured data sources such as social media, news, internal or external documents, images, video, voice, emails, financial data, and operational data. Perform exploratory data analysis, generate and test working hypotheses, and uncover interesting trends and relationships.

• Analyze and model structured data and implement algorithms to support analysis using advanced statistical and mathematical methods from statistics, machine learning, data mining, econometrics, and operations research.

Qualifications:

• Bachelors, Masters or PhD in Computer Science, Engineering, or related fields; PhD preferred. Preferred: Prior exposure to working in technical teams outside classroom setting to deliver business-driven analytics projects using natural language processing, machine learning on unstructured data, and/or information retrieval; multidisciplinary backgrounds.

• Ability to apply artificial intelligence techniques to real-world use cases by: working with the business to understand available resources and constraints around data (sources, integrity, and definitions), processing platforms, and security,; understanding data preparation, machine learning, deep learning, natural language processing; applying working knowledge of performing data science (data discovery, cleaning, model selection, validation, and deployment); coding artificial intelligence methods using object-oriented programming in a software development process; discussing mathematical formulations, alternatives, and impact on modeling approach.

• Ability to utilize a diverse array of technologies and tools as needed, to deliver insights, such as R, Python, Scala, Javascript, Spark, Hadoop and emerging Cloud Capabilities on Azure, GCP or AWS; working knowledge of command-line scripting, data structures, and algorithms; ability to work in a Linux environment.

• Ability to travel up to 80% of the time, depending on project assignments.

• Targeted graduation date Fall 2019 through Summer 2020

Work Authorization

Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.