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Martin Laprise is a Founder and Chief Scientist at Hectiq.AI. He possess expertise in python, natural language processing, physics, data mining, machine learning and 28 more skills. He is proficient in English. Colleagues describe him as "I was fortunate to hire Martin twice - at both Klood and Twenty3. When searching for Klood's first data scientist, it became clear that there are many "theoretical" data scientists out there. Martin stood out from them all because he possessed valuable engineering skills that meant he could take an idea and deliver it all the way from theory through to servers running in AWS. So much data science gets stuck in Jupyter Notebooks or R... with Martin you avoid this and bring data science all the way to production. 10/10 would hire again!" and "Martin is awesome: passionate about data, motivated by challenges, and lots of deep knowledge in important tools in the PyData and Hadoop/Spark ecosystems. Martin was one of my earliest hires for Parse.ly's backend/data team, and kept up with the ecosystem as it evolved quickly alongside our company. He self-instructed in technologies like Pig, Pandas, pyspark, and other tools, and regularly wrote data analyses that became part of our public research or customer-facing products. He also mastered all the various data stores we used, such as MongoDB, Elasticsearch, and Amazon Redshift, so that he could write scripts to pull data for our marketing and product teams, or investigate data discrepancies. He has a boundless curiosity, a strong work ethic, and is not afraid to roll up his sleeves to hack on projects. I highly recommend him."
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Founder And Chief ScientistHectiq.AiQuébec, Qc, Ca -
Founder & Chief ScientistHectiq.Ai Jan 2018 - PresentQuebec, CanadaHectiq AI is an artificial intelligence solutions provider. We research, design & build AI technologies to help our clients solve real-world problems using data. -
Head Of Data ScienceTwenty3 Apr 2017 - Apr 2018London, United KingdomTwenty3 is a sports analytics company providing analytics and predictive models to fans, media outlets and professional clubs. As the Head of Data Science, I built the Data Science Team, put the DS process in place and architect the DS backend to productize the models and analysis produced by the team. We produced a number of interesting tools and models:• Players Transfer monitoring on social media & in the news using various machine learning models and NLP methods for entity extraction, news classifications, etc..• Player Transfer predictive model based on Survival & Bayesian Analysis• Player Performance using regularized linear model• Match Lineup prediction using a Bayesian model based on a Dirichlet process • Players & Teams personas based on Latent Dirichlet Allocation• Match projections model using a Bayesian approach• Match predictive model using the on-the-ball events data modelled as a Markov process & LSTM deep neural networks as a well as a new approach using a reinforcement learning approach (Deep Q-Learning) -
Data ScientistKlood Ltd Apr 2016 - Apr 2017• Build and deployed custom machine learning models in the app using tools like Scikit-Learn, TensorFlow, Keras, Statsmodels, etc.• Designed and implemented the Klood Graph Engine, a graph exploration tool based on Topological Data Analysis methods.• Performed custom in-depth statistical analysis for our clients.• Designed and implemented various NLP systems: - Klood Entities Graph, an entities extraction and exploration tool working at scale - Search query creation assistant based on word embedding methods and discriminative models. -
Data Scientist / Algorithm LeadParsely, Inc. Jan 2013 - Apr 2016Greater New York City AreaParse.ly is a technology company that provides web analytics and content optimization software for online publishers.As the first Data Scientist in the company:• Performed custom in-depth statistical analysis and predictive models for our clients, the marketing and the product team.• Implemented ETL data pipelining and warehousing using Hadoop tools like Apache Spark and Apache Pig.• Architected and implemented our first Yarn Cluster.• Helped developing algorithms for analysis and storage of high volume streaming data using Apache Storm and probabilistic data structures.• Designed and implemented NLP algorithms for our product. -
CtoCrowdbase Feb 2012 - Jan 2013• Validate the technology used in the product and perform the internal due diligence for the seed funding ($ 650k).• Manages development and technical architecture of Crowdbase.• Research and Development of the natural language processing components of Crowdbase.• Designed and developed the recommendation engine algorithms.
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Data ScientistCrowdbase Jun 2011 - Feb 2012Quebec, Canada• Research and Development of the natural language processing components of Crowdbase.• Designed and developed the recommendation engine algorithms.
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Data Scientist & Software EngineerBrightscope Dec 2010 - Jun 2011• Development of financial analytics softwares.• Coding of the Monte Carlo simulations.• Development of a GPU accelerated version of the stochastic simulations. -
Teaching Assistant - Physics DepartmentUniversite Laval 2001 - 2006Design of the experiments about the erbium fiber laser and the erbium amplifier.Assisted students in all aspects of the experimental process including: theory, data acquisition, data analysis, report writing.Correction of the theorical assignments.• Physics of Lasers graduate course• Optics-Photonics II• Optics-Photonics I• Optical Fiber undergraduate course
Martin Laprise Skills
Martin Laprise Education Details
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Physics -
Physics -
Physics
Frequently Asked Questions about Martin Laprise
What company does Martin Laprise work for?
Martin Laprise works for Hectiq.ai
What is Martin Laprise's role at the current company?
Martin Laprise's current role is Founder and Chief Scientist.
What is Martin Laprise's email address?
Martin Laprise's email address is ml****@****ail.com
What is Martin Laprise's direct phone number?
Martin Laprise's direct phone number is +158177*****
What schools did Martin Laprise attend?
Martin Laprise attended Université Laval, Université Laval, Université Laval.
What skills is Martin Laprise known for?
Martin Laprise has skills like Python, Natural Language Processing, Physics, Data Mining, Machine Learning, Monte Carlo Simulation, Matlab, Linux, Nlp, Hadoop, C, C++.
Who are Martin Laprise's colleagues?
Martin Laprise's colleagues are Charles Murphy, Edward Laurence.
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