Data Scientist

Engineering · Edmonton, Alberta
Department Engineering
Employment Type Full time
Minimum Experience Mid-level

Data Scientist


Granify is a rapidly growing technology company at the intersection of e-commerce, machine intelligence, and psychology. We’ve received investment from top investors, built a world-class team and a world-class product, and in the last year alone we generated over $650 million in incremental sales for many of the world's largest retailers! 


We’re searching for an experienced Data Scientist (4+ years of experience) who values mastery, authenticity, and positivity to help build and grow our product. As a key member of our Data Science team, you will work with and analyze vast amounts of behaviour and transaction data, and design and implement algorithms which predict e-commerce shopper actions and needs. This includes - but goes well beyond - recommendations. This is an amazing opportunity to design algorithms which will be responsible for helping and influencing real shoppers across the world in real-time! We have access to and act on millions of shopper sessions per day. If you are a highly technical, hands-on, and mission-driven person who has a passion for solving problems in the area of ML/AI and e-commerce optimization, then this is the role for you.


This is a full-time position. We are centrally located in Edmonton, but remote applications will also be considered.


RESPONSIBILITIES

  • Develop new and improve existing ML models that guide our interactions with shoppers
  • Help design and create ML/AI based tools to interact with shoppers
  • Evaluate performance statistics at an extremely detailed level and present insights and recommendations to teammates.
  • Analyze, interpret and use machine learning and data mining algorithms on the enormous amount of behavioural and transactional data
  • Recommend new experiments supported by your findings and research
  • Dissect online stores’ shoppers data to identify opportunities to increase conversion, order value, lifetime value, and customer delight
  • Write code to implement your experiments
  • Work closely with our developers and engineers to bring your new experiments to life
  • Solve a wide variety of complex problems as they arise that will often require significant analysis of our data, research and deep thinking
  • Participate in brainstorming sessions with your teammates to determine opportunities for improvement and experiments
  • Research, design and prototype intelligent systems with the aim of enhancing online shopper experience.
  • Keep up-to-date with the latest papers in artificial intelligence and machine learning to propose solutions for real problems in e-commerce.
  • Help to build infrastructure to support the evolution of our shopper interaction toolset
  • Collaborate with other DS team members, mentor junior DS,  participate in code reviews, and share knowledge.
  • Participate in active maintenance and code reviews in a large codebase, suggesting and implementing changes as appropriate.
  • Troubleshoot, test, and debug to your heart’s content.


    ABOUT YOU

    • BSc (Msc/Phd preferred) in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, Physics, or a related discipline, with (at minimum) graduate-level courses in machine learning, or equivalent practical experience.
    • At least 4+ years of real-world experience implementing Machine Learning models
    • Comfortable jumping into an existing ML modelling code base
    • Proficient in at least one programming language, preferably Python (focus on ML)
    • Demonstrated ability to apply statistical or data mining techniques to solve real problems
    • Ability to organize, interpret, and analyze large amounts of data
    • Advanced skills and experience in machine learning and data mining
    • Strong research experience in machine learning, preferably in one or more of the following (in no particular order): 
      • Unsupervised and Supervised Learning
      • Reinforcement learning
      • Recommender and/or ranking systems
      • Deep learning and deep generative models
      • Computer vision
      • NLP
    • Intimately familiarity with the DS workflow: 
      • Data gathering and cleaning
      • Feature engineering
      • Model design, coding, hyperparameter tuning and validations
    • Proficient in deep learning frameworks like Tensorflow, PyTorch, etc. and scientific computing packages like NumPy. Able to implement an algorithm as described in an academic paper using these frameworks in quality code.
    • Knowledge of various ML and statistical tools and libraries (e.g. TensorFlow, sciPy, R, and similar)
    • Good intuition for applying ML/AI theory to make business-oriented products with minimal guidance.


    BONUS EXPERIENCE

    • Experienced using shopper data
    • Worked with ‘Big data’ 
    • Hands-on Knowledge of distributed computing frameworks (e.g. Spark, AWS, Flink)
    • Experience in online advertising/marketing analytics, behavioral targeting or web analytics
    • Experience with distributed databases


    OUR TECH STACK

    We are using AWS cloud and the ML stack includes Python, TensorFlow, Spark, DataBricks and Hadoop. We have dedicated Data Engineers and Software Developers who provide support and tools needed for research and help with implementation of research outcomes.


    ABOUT GRANIFY

    Granify merges machine intelligence and digital psychology to automatically increase sales for retailers. This is the future and it’s an exceptionally interesting world to delve into every day! Our mission is to provide the ultimate experience for every shopper at any given point in time and, in doing so, completely redefine the trillion-dollar e-commerce market. We hope you can help us achieve this ambitious mission! 


    Granify is backed by early investors in Tesla, Facebook, SpaceX, AirBnB, Pinterest, Palantir, Alibaba, and Yelp and won Top E-Commerce Solution and Top Digital Startup at the DAA Awards! 

    Thank You

    Your application was submitted successfully.

    • Location
      Edmonton, Alberta
    • Department
      Engineering
    • Employment Type
      Full time
    • Minimum Experience
      Mid-level