Associate Data Scientist - AI Platforms & NLP 2020 National

Responsibilities & Qualifications

KPMG is currently seeking an Associate for our Lighthouse - Data & Analytics Data Science AI Platforms and Natural Language Processing 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 while working across different areas (risk management, financial services, mergers and acquisitions, 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; communicate results and educate others through insightful visualizations, reports, and presentations.

• Build ingestion processes to prepare, extract, and annotate natural-language data from a variety of unstructured sources (social media, news, internal/external documents, images, video, voice, emails, financial data, and operational data).

• Leverage a variety of tools and approaches to solve complex business objectives, from Statistical Natural Language Processing, Information Retrieval/Extraction, Machine Learning/ Deep Learning, Image Processing, Rules Engines, Knowledge Graphs, and Semantic Search.

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

• Refactor, deploy and validate models; work with clients to validate performance metrics, and sample output to drive towards a business-first solution; utilize APIs, platforms, containers, multi-threading, distributed processing to achieve throughput goals.

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.

• Fluency in Python; proficiency in AI related frameworks (Pandas, NLTK, Spacy, Scikit-Learn, Tensorflow); working knowledge of platforms (Google Cloud, Azure, and Amazon Web Services); ability to pick up new languages and technologies quickly and work efficiently under Unix/Linux environment and familiarity with source code management systems like GIT; ability to work with a variety of databases (SQL, ElasticSearch, Solr, Neo4j); and understanding of development practices such as testing, code design, complexity, and code optimization..

• 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.