Thomson Reuters-posted 3 months ago
$101,640 - $188,760/Yr
Full-time • Mid Level
Burlington, VT
5,001-10,000 employees
Publishing Industries

The Data Scientist will be responsible for managing, understanding and analyzing in-house and customer data - including text mining, developing predictive systems, risk scoring, creating efficient algorithms, data quality improvement and other related activities. This individual will work closely with the TRSS Analysts to drive, identify, evaluate, design and implement statistical analyses of gathered open source, proprietary, and customer data to create analytic metrics and tools to support TRSS analysts, customers and existing product offerings. Successful candidates will have the opportunity to contribute directly to the features and capabilities deployed in our applications. They will work with customers to assist in gathering requirements and contributing to Statements of Work (SOWs) for new sales or POCs and executing design post sale while getting deeply involved into the delivery of the proposed solutions. The role will interface with the customer and provide continuity of technical and data-exploration expertise to ensure we are delivering a workable solution that meets the customer requirements and technical capabilities. The position requires a proactive, mission-oriented person who strives to produce the best possible work for the customer.

  • Define, manipulate, aggregate and use both structured and unstructured 'big data' in order to support descriptive and predictive analytics across the businesses.
  • Collaborate with scientists, product groups and content groups to perform 'big data' aggregations, symbology mapping, and manipulations of important data-sets.
  • Perform statistical (and machine learned) analyses on data to serve business purposes.
  • Narrate stories (sometimes to a non-technical audience) about our content and processes by data analysis and visualization.
  • Define and develop software for the analysis and manipulation of large and very large data-sets.
  • Guide the architecture of 'big-data' business processes with an eye towards robustness, parsimony and reproducibility.
  • A bachelor's or master's degree in a quantitative field (e.g., statistics, computer science, mathematics physical/biological sciences, or GIS).
  • 3-5 years of experience with data cleaning, analysis, programming, and reporting of results to internal or external stakeholders (education can substitute for some years of experience).
  • Programming skills in one or more major programming languages (Python/R/Java).
  • A good understanding of distributed computing concepts.
  • Experience facilitating and gathering input from subject matter experts.
  • Excellent understanding of ML, NLP, and statistical methodologies.
  • Strong planning, time management, and organizational skills.
  • Ability to obtain and maintain a U.S. national security clearance.
  • Big Data analytics experience (preferred, but not required).
  • Previous experience with data modeling for graphs (preferred, but not required).
  • Experience with search engines, classification algorithms, recommendation systems, and relevance evaluation methodologies (preferred, but not required).
  • Hybrid Work Model: Flexible hybrid working environment (2-3 days a week in the office).
  • Flexibility & Work-Life Balance: Supportive workplace policies for personal and professional responsibilities.
  • Career Development and Growth: Continuous learning and skill development opportunities.
  • Industry Competitive Benefits: Comprehensive benefit plans including flexible vacation, mental health days, retirement savings, and tuition reimbursement.
  • Culture: Award-winning reputation for inclusion and belonging.
  • Social Impact: Opportunities for community involvement and pro-bono consulting projects.
  • Making a Real-World Impact: Helping customers pursue justice, truth, and transparency.
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