Location(s)

One Corporate Center 20 Church St, Hartford, CT 06103

Position Type

Full Time - Regular

Job Description

Data Scientist - 17-17679

This role can be located in Hartford, CT, Houston, TX OR
New York, NY with travel to Hartford and Houston

The Data Scientist for LegalVIEW Analytics is responsible for setting and executing the vision for our LegalVIEW data set, the world’s largest source of legal performance data, which powers benchmarking intelligence, predictive and analytical models, and management insights embedded in Wolters Kluwer ELM Solutions’ product portfolio. Supporting the product management, marketing, engineering and sales and professional services teams, the Data Scientist will forecast future business challenges and opportunities using big data and big-picture trends.

Ideally, this person has Legal industry knowledge or subject matter expertise, a statistical analysis and/or data science background, and basic understanding of computer science in order to extract information from the data to answer customer business questions, generate insights, and communicate them back to clients.

Ultimately, this person serves as the translator between Audience & Data, the Storyteller & Thought Leader communicating trends, insights and LegalVIEW value proposition to prospects, customers, partners, industry and internal audiences. The successful candidate will take a pragmatic, applied, scientific approach communicate results in a simple, easy to understand way.
Leveraging advanced data analysis skills, the candidate will create innovative approaches to answer our clients’ most relevant questions, extrapolate data to inform and drive strategic roadmaps.

Qualifications

Minimum Qualifications:
Education:
• BS in Computer Science/Machine Learning or strong technical/programming (SQL, Python, R, Java, etc...)
• MS or Ph.D. in Statistics, Data Science or a quantitative field preferred

Essential Duties & Responsibilities:
• Work with subject matter experts, perform data studies and analysis to identify meaningful business opportunities.
• Drive product roadmaps based on analytics and data strategies.
• Work with Architects and Development teams to ensure future proof infrastructures that can support analytics and data use-cases.
• Support product management, teams marketing, engineering and sales and professional services to identify opportunities and trends for using big data.
• Interface with product team to develop requirements and analyze the tests/data resulting from machine learning activities. Implement Data Science methodologies at scale over large datasets.
• Apply machine learning and AI algorithms to analyze the data and generate models that can be applied to legal operations.
• Identify and analyze additional data sources to augment the production opportunities.
• Rapidly prototype data science and AI solutions for integration with WK ELM Solutions products and services.
• Communicate insights and findings to internal and external stakeholders
• Enjoy working and learning in a fast paced and rapidly evolving environment

Preferred Experience:
• Market understanding of Corporate Legal, Law Firm, Insurance and Claims organizations
• Experience applying data science in legal industries
• Hands-on experience applying Big Data / Map Reduce techniques, including Spark and Hadoop distributed-computing platforms, to real-world problems.
• Experience applying AI (including but not limited to Automated Planning, NLP, Multi-Agent Systems, etc.) or Operations Research techniques.
• Familiarity and comfort with SQL and relational databases.
• Knowledge of NoSQL database technologies.
• Experience with cloud computing platforms
• Experience with Hadoop and related Big Data technologies

Other Knowledge, Skills, Abilities or Certifications:
? Strategic thinker
? Strong interpersonal, communication (verbal and written), and speaking skills
? Ability to gain buy-in and alignment across key executive stakeholders
Ability to travel both domestically & internationally, up to 20%

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Confirmed 20 hours ago. Posted 30+ days ago.

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