Manage, understand and analyze in-house and customer data, including text mining, predictive systems, risk scoring, efficient algorithms, and data quality improvement
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 and customers
Collaborate with scientists, product groups, content groups, and TRSS Analysts to perform big data aggregations, symbology mapping, and data manipulations
Contribute directly to features and capabilities deployed in applications and work with customers to gather requirements and contribute to Statements of Work (SOWs) and execute post-sale design and delivery
Perform statistical and machine learned analyses to serve business purposes and narrate stories through 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 focus on robustness, parsimony and reproducibility
Work with interdisciplinary engineering and research teams to design, build and deploy data analysis systems for large data sets
Establish scalable, efficient, automated processes for model development, validation, implementation, and large-scale data analysis
Develop metrics and prototypes to drive business decisions and provide thought-leadership on diverse projects
Research and identify AI methods (including ML and NLP) and identify new applications for TRSS content sets
Requirements
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)
Excellent understanding of ML, NLP, and statistical methodologies
Experience with data cleaning, text mining, developing predictive systems, risk scoring, creating efficient algorithms, and data quality improvement
Good understanding of distributed computing concepts
Experience facilitating and gathering input from subject matter experts
Ability to test ideas and adapt methods quickly end to end from data extraction to implementation and validation
Strong planning, time management, and organizational skills
Ability to obtain and maintain a U.S. national security clearance
Preferred: Big Data analytics experience
Preferred: Experience with data modeling for graphs
Preferred: Experience with search engines, classification algorithms, recommendation systems, and relevance evaluation methodologies
Benefits
Hybrid Work Model: flexible hybrid working environment (2-3 days a week in the office depending on the role)
Flex My Way policies, including work from anywhere for up to 8 weeks per year
Flexible vacation, sick and safe paid time off, and paid holidays (including two company mental health days)
Two company-wide Mental Health Days off and access to the Headspace app
Retirement savings with 401(k) plan and company match
Health, dental, and vision insurance
Disability and life insurance
Parental leave and sabbatical leave
Annual Bonus eligibility (based on enterprise and individual performance)
Tuition Reimbursement and Grow My Way career development programs
Employee incentive programs and resources for mental, physical, and financial wellbeing
Optional hospital, accident and sickness insurance (employee-paid)
Optional life and AD&D insurance (employee-paid)
Flexible Spending and Health Savings Accounts
Fitness reimbursement
Employee Assistance Program
Group Legal Identity Theft Protection (employee-paid)
Access to 529 Plan
Commuter benefits
Adoption & Surrogacy Assistance
Employee Stock Purchase Plan
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data analysistext miningpredictive systemsrisk scoringefficient algorithmsmachine learningnatural language processingdata cleaningprogramming (Python)programming (R)