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We are looking for a Data Scientist that will help us make smarter data-based decisions to deliver even better products to our customers. This role’s primary focus will be in applying data mining techniques, conducting statistical analysis, and building high-quality prediction systems integrated with our products. They will uncover hidden opportunities in the course of mining, interpreting, and cleaning data. The ideal candidate will have mathematical and statistical expertise, as well as natural curiosity and the ability to work in a dynamic, research-oriented group involved in several concurrent projects. 

Typical Duties and Responsibilities

  • Serve as the lead data strategies to identify and integrate new datasets that can be leveraged through our product capabilities
  • Work with the engineering team to develop data products
  • Select features and building and optimize classifiers using machine learning techniques
  • Identify relevant data sources and sets to mine for internal or client business needs
  • Collect large structured and unstructured datasets and variables
  • Devise and utilize algorithms and models to mine big data stores
  • Perform data and error analysis to improve models
  • Clean and validate data for uniformity and accuracy
  • Analyze data for trends and patterns and interpret data with clear objectives in mind
  • Implement analytical models in production in collaboration with software developers and machine learning engineers
  • Create automated anomaly detection systems and track their performance
  • Research and devise innovative statistical models for data analysis
  • Use analytics to derive meaningful insights and enable smarter business processes
  • Stay up-to-date with technical and industry developments

Education

  • Bachelor’s degree in statistics, applied mathematics, or a related field

Required Skills and Experience

  • 5+ years of experience in data science
  • 2+ years of experience in project management 
  • Experience with data mining
  • Experience in pattern recognition and predictive modeling 
  • Experience with Excel, PowerPoint, Tableau, and SQL
  • Experience with programming languages, including Java and Python
  • Experience with common data science toolkits, such as R, Weka, NumPy, or MatLab
  • Experience with data visualization tools such a D3.js or GGplot
  • Experience with NoSQL databases
  • Thorough knowledge of machine learning techniques and algorithms
  • Knowledge of mathematics and statistical analysis
  • Knowledge of applied statistics, including distributions, regression, and statistical testing
  • Strong communication skills

Preferred Qualifications

  • Relevant professional certifications