Data Scientist

DLA Piper•Short Hills, NJ

4d•$112,879 - $179,481•Hybrid

About The Position

This position is responsible for data collection, data exploration, and using large data sets to find opportunities for improving business outcomes. The role involves designing data modeling processes to create algorithms and predictive models, performing custom analysis, and using modeling to drive business results with data-based insights and testing the effectiveness of different courses of action.

Requirements

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.
5 years of relevant experience in applying data science techniques to business functions.

Nice To Haves

A specialization in machine-learning, artificial intelligence, cognitive science or data science is preferred.
Experience in a professional services or law firm is preferred.

Responsibilities

Works with internal stakeholders and clients to identify opportunities for leveraging organizational data to drive business solutions.
Prioritizes, scopes and manages data science projects for internal stakeholders and clients.
Mines and analyzes data to drive optimization and improvement of product development, marketing techniques and business strategies.
Assesses the effectiveness and accuracy of new data sources and data gathering techniques.
Applies the principles of artificial intelligence, database systems, human/computer interaction, numerical analysis, and software engineering. Identifies patterns and looks for opportunities for optimization.
Develops custom data models and algorithms to apply to data sets.
Uses predictive modeling to increase and optimize client opportunities and business outcomes.
Writes computer programs and analyzes large datasets to uncover answers to complex problems.
Develops testing frameworks and tests model quality.
Coordinates with different functional teams to identify and implement models and monitor outcomes.
Develops processes and tools to monitor and analyze modeling performance and data accuracy.
Establishes best practices for data analysis and reporting.
Other duties as assigned.