Data Scientist III

Offer by LexisNexis

algorithm

java

hadoop

About this job

Job type: Full-time
Role: Data Scientist



Technologies

algorithm, java, hadoop



Job description

S

Data Scientist III

At LexisNexis, we develop the legal profession?s most innovative products for data analysis, visualization, and research - uncovering insights about judges? rulings, revealing critical cases, enabling lawyers to make data-driven decisions, and more. LexisNexis seeks a Senior Data Scientist to join our rapidly growing team. As a senior member of the Data Science team, you will design systems to tackle tough problems in the legal domain and expand our award-winning products.

ACCOUNTABILITIES

  • Evaluate, fix, and help in the maintenance our data assets and training/evaluation data sets
  • Develop and implement scalable machine learning-based solutions
  • Pariticpate in model reviews with key stakeholders, including stakeholders with limited statistical backgrounds from among that set
  • Work with product leaders to apply data science solutions
  • Maintain current knowledge-base of best-in-class algorithms, API's, and open-source methods and be able to quickly evaluate alternatives
  • Translate complex business requirements into actionable stories with reasonable time estimates
  • Participate in knowledge sharing sessions (e.g. Guilds and Chapters)


DATA SCIENCE AND NLP SKILLS

  • Formal training in dimensionality reduction, clustering, and sequence classification algorithms
  • 3+ years experience using Machine Learning package ScikitLearn
  • 3+ years experience using NLP methods  such as OpenNLP, StanfordNLP, Mallet, LDA, word2vec

PROGRAMMING SKILLS

  • 3+ years recent coding experience using Python AND/OR (Java OR Scala)
  • SQL programming experience

CLOUD AND DATABASE SKILLS

  • 1-3 years experience developing in AWS
  • 1-3 years experience working in high-performance / large-scale (big data) computing systems (e.g Hadoop, Spark)

 TEAM AND SOCIAL SKILLS

  •  Strong collaboration and team skills (DIR/MGR)


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