Data Scientist (Contract) – IT-Online

  • Maintain clear and consistent communication, both verbal and written, to understand data needs and report results
  • Create clear reports that tell compelling stories about how customers or clients are doing business with the company
  • Assess the effectiveness of data sources and data collection techniques and improve data collection methods
  • Conduct research from which you will develop prototypes and proof of concepts
  • Establish new systems and processes and seek opportunities to improve data flow
  • Assess new and emerging technologies
  • Represent the company at external events and conferences
  • Build and develop relationships with clients
  • Identify valuable data sources and automate collection processes
  • Undertake pre-processing of structured and unstructured data
  • Analyze large amounts of information to discover trends and patterns
  • Build predictive models and machine learning algorithms
  • Combine models with assembly modeling.
  • Work with stakeholders across the organization to identify opportunities to leverage enterprise data to drive business solutions.
  • Extract and analyze data from company databases to optimize and improve product development, marketing techniques and business strategies.
  • Assess the effectiveness and accuracy of new data sources and data collection techniques.
  • Develop custom data models and algorithms to apply to datasets.
  • Use predictive modeling to augment and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.
  • Develop the company’s A/B testing framework and test the quality of the model.
  • Coordinate with different functional teams to implement models and monitor results.
  • Develop processes and tools to monitor and analyze model performance and data accuracy.


  • 5-7 years of experience manipulating datasets and creating statistical models
  • Strong problem-solving skills with a focus on product development
  • Experience using statistical computer languages ​​to manipulate data and derive insights from large data sets
  • Experience working and building data architectures
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their actual advantages/disadvantages
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical testing and proper usage, etc.) and experience with applications
  • Excellent written and verbal communication skills for coordination between teams
  • Knowledge and experience of statistical and data mining techniques
  • Experience in querying databases and using statistical computer languages
  • Experience using web services
  • Experience building and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
  • Experience analyzing data from third-party vendors
  • Experience with distributed data/computing tools
  • Experience in visualizing/presenting data for stakeholders

Qualifications A diploma, master’s or doctoral degree in statistics, mathematics, computer science or another quantitative field, with the following subjects:

  • Computing
  • Data Science/Computer Science and Data Science
  • Engineering
  • Mathematics and operations research
  • Physics

Technical skills

  • Statistical and computer analysis
  • machine learning
  • deep learning
  • Processing large data sets
  • Data visualization
  • Data Conflict
  • Math
  • Programming

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Sean N. Ayres