layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

LAYIQ - Data Scientist, Applied AI Solutions at DLA Piper

Develops and applies algorithmic testing methods to evaluate AI systems, models, and tools for bias, accuracy, reliability, robustness, and performance.
Creates novel testing techniques, metrics, and evaluation frameworks for emerging AI systems and risks when established methods are insufficient.
Translates legal, regulatory, and business requirements into analytic objectives, testable criteria, data specifications, and practical technical solutions.
Works with internal stakeholders, lawyers, and clients to identify opportunities to leverage organizational and client data to address business, legal, investigative, and regulatory needs.
Prioritizes, scopes, and manages multiple concurrent data science projects and client engagements, with accountability for delivery quality, timelines, measurable business outcomes, and commercially valuable solutions.
Designs, builds, deploys, and supports production machine learning models and data science solutions at scale, including solutions for privilege review and related legal workflows.
Designs representative test datasets, test cases, benchmarks, validation protocols, and monitoring approaches; documents methodologies, results, limitations, and recommendations.
Assesses the quality, completeness, representativeness, and accuracy of structured and unstructured data sources and data-gathering techniques.
Uses Python and SQL extensively to build models, data pipelines, testing tools, and analyses.
Manages structured and unstructured datasets in secure enterprise environments and works with Azure AI services or comparable enterprise cloud and data platforms.
Develops custom data models, algorithms, and predictive solutions that improve client outcomes and support data-driven decision-making.
Coordinates with legal, technical, and business teams to implement solutions, monitor outcomes, and refine models and testing methods.
Communicates methods, findings, risks, and actionable insights to technical and non-technical audiences through client-ready analyses, documentation, and presentations.
Establishes and applies best practices for reproducible analysis, model governance, quality assurance, data protection, and reporting.
Supports the delivery of revenue-generating client solutions within consulting or professional-services delivery models.
Other duties as assigned.
Desired Skills
Experience in a law firm or other legal-services environment is preferred.
Proven experience delivering revenue-generating client solutions with measurable outcomes, managing multiple concurrent client engagements, and operating within consulting or professional-services delivery models.
A specialization in machine-learning, artificial intelligence, cognitive science or data science is preferred.
Must be self-driven, curious and creative.
Experience must include creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, data mining techniques, etc.
Experience with most or all of the following basic data science tools: Python, R, SQL, SAS, NLTK, Scikit-Learn, Excel, Tableau, Power BI, and Jupyter; Basic data science concepts: probability, statistics, hypothesis testing, machine learning, natural language processing, predictive modeling, data visualization; and Big data tools: Hadoop, Azure, etc.
Must be adept in agile methodologies and well-versed in machine learning, artificial intelligence and constructing data science pipelines.
Demonstrated presentation skills along with strong business acumen.
Ability to communicate actionable insights using data, often for a non-technical audience.
Significant hands-on coding experience in Python and SQL is required, 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 enterprise cloud and data platforms is required.
Must be able to design and execute algorithmic testing of AI systems, including bias and accuracy assessments, and create novel evaluation methods when established approaches are insufficient.
Must be able to translate legal and regulatory requirements into analytic methods, testable criteria, and defensible technical documentation.
Preferred experience includes delivering data science solutions within legal, eDiscovery, investigations, privilege review, or regulatory compliance environments.
Minimum Education
Bachelor's degree in computer science, data science, statistics, applied mathematics or related field.
Minimum Years of Experience
5 years of relevant experience applying data science and machine learning techniques to complex business problems, including building and deploying production models at scale.
Essential Job Expectations
All DLA Piper employees are expected to demonstrate excellence in how we serve our clients and develop our people, upholding our firm values as part of our culture. Specific expectations include:
Communicate effectively, both verbally and in writing, with clients, lawyers, business professionals, and external audiences.
Produce high-quality work and respond to correspondence in an efficient, timely, and professional manner.
Meet deadlines, manage competing priorities, and commit to meeting high standards.
Comply with firm policies and procedures.
Maintain confidences as required in a law firm environment.
Physical Demands
Sedentary work: This is primarily sedentary work, requiring occasional exertion of up to 10 pounds of force to lift, carry, push, pull, or move objects. The role involves sitting for extended periods, with occasional walking and standing, and occasional travel, both domestic and international.
Work Environment
The selected candidate will have the opportunity for a hybrid work arrangement combining remote and in-office work. The specific arrangement will be determined at the time of hiring and may be modified at the firm's discretion.

Data Scientist, Applied AI Solutions

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