• What is the value of Data Science?

    Data Science can help businesses improve their bottom line by helping solve their particular challenges and enabling better decision making. For instance, businesses can benefit from extracting more value from their data to:
    • Improve the understanding and characterisation of their business processes to identify efficiency gains,
    • Profile customers and monitor customer changes over time,
    • Identify the most valuable market segments to target,
    • Provide their clients with added services developed using models leveraging data aggregated over multiple clients,
    • Use predictive analytics for forecasting or real-time alerts…
    More data is being created and in new ways. Using this increasingly diverse data will provide advantages for early adopters. At Iris Data Science, we provide a suite of services to record, store, transform, combine, clean and analyse data, provide predictive analytics, data visualisations and dashboards, and real-time alerts to extract valuable insights for businesses.

  • Latest News

    Unlocking Curious Minds – project showcase

    In December the team from Iris Data Science completed the Unlocking Curious Minds "Otago geological hazards science and technology engagement using internet of things and data science" project. The project concluded with a showcase of all the activities, see the flier: UCM 2017 Showcase. We have enjoyed working with GeoID, Amadeo Ballesteros and others, engaging with over 1,000 young people in Otago talking about  geohazards, technology and data science. The following resources have been generated and are available online:  


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  • Our Team

    Benoit is an experienced data scientist, with projects involving large datasets, visualisations and sensor data.

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    Benoit Auvray

    Director and Lead Scientist

    Greg Peyroux is the IT & Managing director at Iris Data Science and has over 15 years’ experience as an ICT leader, manager and strategist.

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    Greg Peyroux

    Managing and IT Director

    Masha Mikhisor is a computer vision and machine learning engineer at Iris Data Science. Masha has experience in applying different supervised and unsupervised learning methods for real time image recognition tasks.

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    Masha Mikhisor

    Computer Vision and Machine Learning Engineer

    Philippe Mourot is an experienced environmental and computer scientist with significant experience with monitoring systems, including setting up over 80 Internet of Things networks.

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    Philippe Mourot

    Geophysics and IoT Consultant

  • Our Clients

    What clients say about Iris Data

    Decision Sciences, Software Engineering & Analytics


    Working with Greg over a number of years on the development of nutrient management software, I found Greg to be passionate about his work, very easy to deal with and accommodating to others ideas and decisions. Greg kept the momentum going which was particularly important where obstacle’s arose, while providing the technical guidance to see the project through to completion.


    Jim Risk Sci Extn Nutrient Dynamics Specialist, Ballance Agri Nutrients

    Sports Analytics


      Iris Data Science provided the ODT with picks for the Super Rugby competition during the 2017 season and its accuracy could not be faulted.

    The LAMP  (Losing & margin predictor), as it was known, easily beat out the two human selectors, and brought something different and new to the selection table every week.   


    Steve Hepburn Sports Editor, Otago Daily Times

  • Contact Us

      + 64 21 262 9769

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