Data Scientist, Applied AI Solutions

Shape applied AI that holds up in the real world. In a hybrid role based in Reston, VA, DLA Piper’s Data Scientist, Applied AI Solutions collects, explores, and analyzes large, complex datasets to improve business and client outcomes. You will design and deploy machine learning solutions while translating legal, regulatory, and business needs into practical analytic and testing approaches, including bias and accuracy evaluation.

What you’ll do

• Develop and apply algorithmic testing methods to evaluate AI systems and models for bias, accuracy, reliability, robustness, and performance.
• Create novel testing techniques, metrics, and evaluation frameworks for emerging AI systems and risks when established methods are not sufficient.
• Translate legal, regulatory, and business requirements into analytic objectives, testable criteria, data specifications, and defensible technical solutions.
• Partner with internal stakeholders, lawyers, and clients to identify opportunities to leverage organizational and client data for business, legal, investigative, and regulatory needs.
• Prioritize, scope, and manage multiple concurrent data science projects and client engagements, with accountability for delivery quality, timelines, measurable business outcomes, and commercially valuable solutions.
• Design, build, deploy, and support production machine learning models and data science solutions at scale, including solutions related to privilege review and related legal workflows.
• Design representative test datasets, test cases, benchmarks, validation protocols, and monitoring approaches; document methodologies, results, limitations, and recommendations.
• Assess data quality, completeness, representativeness, and accuracy across structured and unstructured sources and data-gathering techniques.
• Use Python and SQL extensively to build models, data pipelines, testing tools, and analyses.
• Manage structured and unstructured datasets in secure enterprise environments and work with Azure AI services or comparable enterprise cloud and data platforms.
• Build custom data models, algorithms, and predictive solutions that improve client outcomes and enable data-driven decision-making.
• Coordinate across legal, technical, and business teams to implement solutions, monitor outcomes, and refine models and testing methods.
• Communicate methods, findings, risks, and actionable insights to technical and non-technical audiences through client-ready analyses, documentation, and presentations.
• Apply best practices for reproducible analysis, model governance, quality assurance, data protection, and reporting.
• Support delivery of revenue-generating client solutions within consulting or professional-services delivery models.

What you bring

• Minimum 5 years of experience.
• Bachelor’s degree in computer science, data science, statistics, applied mathematics, or a related field.
• Experience creating and using advanced machine learning algorithms and statistics (for example: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, data mining techniques).
• Experience with most or all of: Python, R, SQL, SAS, NLTK, Scikit-Learn, Excel, Tableau, Power BI, and Jupyter, plus data science concepts (probability, statistics, hypothesis testing, machine learning, natural language processing, predictive modeling, data visualization) and big data tools (for example Hadoop, Azure).
• Adept in agile methodologies and experienced building data science pipelines in machine learning and AI.
• Significant hands-on coding in Python and SQL, including building, deploying, and supporting production machine learning models at scale.
• Experience managing structured and unstructured datasets in enterprise environments and working with Azure AI services or comparable platforms.
• Ability to design and execute algorithmic testing for AI systems, including bias and accuracy assessments, and to create new evaluation methods when needed.
• Ability to translate legal and regulatory requirements into analytic methods, testable criteria, and defensible technical documentation.

Technologies

Python, SQL, R, SAS, NLTK, Scikit-Learn, Excel, Tableau, Power BI, Jupyter, Hadoop, Azure, Azure AI services

Compensation and benefits

The expected hiring range is $129,808 - $206,399 per year, depending on geographic location, experience, skills, education, and qualifications. Benefits include medical, dental, and vision insurance and a 401(k) retirement plan, plus additional benefits.

Location and work model

This position can sit in any of DLA Piper’s U.S. offices and offers a hybrid work schedule. The selected candidate will have a hybrid arrangement combining remote and in-office work, determined at hiring and subject to modification by the firm.

Application details

• Apply directly online.
• Application materials sent via email will not be accepted.
• Agency applications will not be considered.
• No immigration sponsorship is available.
• Reasonable accommodations may be made upon request; for accommodations, contact [email protected].

Equal Employment Opportunity: DLA Piper provides a concise overview of the role; duties, requirements, and expectations may change at the firm’s discretion. This job description does not alter the at-will nature of employment.