Startup Careers

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Applied Research Scientist - Time Series at Element AI
Montreal, CA / Toronto, CA

As an applied research scientist at Element AI, you will sit in a cross-functional team with several other people with a diversity of skill sets and you will enjoy a unique opportunity to use your creativity towards applying cutting edge machine learning methods to problems with significant impact on the users of our products.

What you’ll do

You will be confronted with real-world challenges and datasets, and you will need to use your expertise and creativity to apply existing methods and develop new ones to solve these problems in a practical and scalable way. You will be called upon to assess possibilities and provide ideas and input into product design choices. This will involve understanding your customer (internal or external) needs and translating them into solutions that address those needs.

You will be expected to both do the necessary research to propose appropriate models/techniques and to have the necessary expertise to implement and train the models yourself. Where useful, you will not hesitate to employ classical forecasting methods, but you are enthusiastic about the idea of pushing the boundaries of deep learning and AI.

Finally, you will be expected to embrace the fact that the value of your work is ultimately reflected in the impact it has on the end-customers using our products and to find ways of measuring that impact as an integral part of your mission.

What we’re looking for

You have significant experience with time series analysis or signal processing from either a forecasting or anomaly detection perspective. You also have an understanding or significant interest in the underlying theory of machine learning or related AI field. This expertise can come from extensive studies, previous industrial experience or awesome self-taught projects you have done on a personal basis. You are comfortable expressing ideas into code and do not mind getting your hands dirty in various coding and engineering tasks.

You understand that running a model on the varied and often noisy data that arise in a commercial context differs significantly from running it on a clean academic dataset and that modifying a model or technique to work in that setting can be a significant and sometimes frustrating challenge. You embrace this challenge and may even have previous experience tackling it.

You learn autonomously and will enthusiastically stay up to date with the literature and techniques of your field while participating in the various learning opportunities we offer.

What is specific about this posting

The ideal candidate would have experience or familiarity with topics such as

  • Time series decomposition
  • Smoothing and forecasting
  • Imputation
  • Spectral analysis
  • Stochastic processes
  • Various time series models (ARIMA, ETS, ARCH, VAR, etc).

If you have a background in statistics and are comfortable with fundamental concepts as they relate to time series modeling, or you have a background in machine learning with strong statistical background and in-depth knowledge of sequence modeling, you would make a great candidate.

Your mandate may begin with you working on a problem in the field of demand planning for a specific project. Previous experience in this field will be a plus but is not mandatory.

What we offer for your valuable work:

  • Open and inclusive company culture
  • Worldwide competitive salary
  • Highly dynamic, innovative, and passionate teams
  • Participation in the company's success through our Employee Stock Option Plan
  • Participation in company employee benefits program
  • Flexible hours (outside of core hours)
  • And lots of nice perks! (food, activities, social events, corporate goodies, fun in general, etc.)

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.