Data Scientist (North America | Remote | Work From Home)

Job Location CA-ON-Ottawa
Posted Date (MM/DD/YYYY) 3 weeks ago(1/31/2018 1:11 PM)
Requirement Number
Location Other
Location Other
Remote/Work from home option-
Location Other
Job Type
Full Time
Career Level
Expert, Intermediate, Senior
Time Zone
Job Category
R&D / Engineering

Job Description

Data Scientist - Machine Learning

Ottawa, ON or Remote / Work from home EST timezone


Why Pythian?

Pythian is a intergalactic technology company based in Ottawa, ON,  who has awesome hitchhikers doing all it takes to help our clients to win through data insights. You would be joining the Data Science team delivering applied machine learning data products to customers and building the Pythian data science product making this delivery consistent and efficient. Pythian specialize in designing, implementing, and managing systems that directly contribute to revenue and business success. We help companies adopt disruptive technologies such as advanced analytics, big data, cloud, databases, DevOps and infrastructure management to advance innovation and increase agility. Our 20 years in data, commitment to hiring the best talent, and our deep technical and business expertise allow us to meet our promise of using technology to deliver the best outcomes faster. More than just a job we hire people who love what they do!


The Work

These are not academic research projects (like finding the true amount of stardust in a glass of Pan Galactic Gargle Blaster or even finding The Answer) - you will be building applied machine learning systems that generate tangible value for the customers (like failure probability of the Improbability Drive coming out of a leap). At the same time you are part of the team that builds our own product pursuing idealistic vision of eventually automating ourselves out of own job. You will be working on all aspects of data science:

  • To give you an idea… example projects we tackle:
    • Dating site matching optimization
    • Predict failures of natural resources mining equipment and optimize maintenance
    • Detect damage of wind turbine components
    • Credit cards customer churn prediction
    • Subscription conversion optimization
    • Radio frequency bands capacity use prediction and optimization
    • Audio stream processing - language detection and speakers detection
  • Generally working on two-three customer projects at a time combined with some pre-sales solution engineering and contributing to our own data science product
  • Learn and understand business domains and translate use cases into machine learning speak (Babelfish hasn’t got there yet).
  • Assess datasets for feasibility of use for machine learning purposes (with the understanding that sometimes data is ‘on display’ in a cellar, with the lights out and the stairs missing, at the bottom of a locked filing cabinet stuck in a disused lavatory with a sign on the door saying ‘Beware of the Leopard’).
  • Create and automate feature extraction and engineering methods.
  • The modelling complexity ranges from working with clean structured data to messy unstructured data, and from applying simple but proven algorithms (linear models, random forests) to complex models (custom deep learning architectures, novel approaches to sequence modeling, model stacking, reinforced learning, transfer learning).
  • Turning ML models and other algorithms into resilient decoupled production systems exposing business specific data insights API embeddable into customers’ products.
  • Paranoidal instrumentation and automation of all aspects of the applied machine learning process, from feature engineering and model building through pipelining for performance tuning and further model performance measurements after deployment.
  • While we have a team of Big Data engineers who are specialized in building hyperspace cloud data bypasses, some heavy data lifting is in order, at times.
  • The world goes digital so we are all over the universe. However, at times, you would hitch a ride to see a client (and check out a new galaxy as a bonus).


The ideal you

  • You have an applied science degree and 3+ years work experience with software development in which you achieved more than average people do in 10+
  • You have complete understanding and heavy practical application of machine learning principles. You do not compromise on testing and validation approaches because you know that Vogons will destroy your planet if you do.
  • You are knowledgeable about a wide range of models, understand the pros and cons of multiple suitable model for a given problem, and have practical experience choosing, using, and tuning a number of them. This includes both supervised and unsupervised methods, clustering models, anomaly detection methods, common regression and classification models (linear models, tree-based models, etc.), NLP and/or sequence based learners, and various modern neural network architectures (CNNs, RNNs, etc.).  
  • You are deep into one or more areas and frequently help other team members in your domain of specializations. We are not a bunch of single heroes - we work as a team (think mixture-of-experts model).
  • You are a master of processing data with Python (we are a Python shop so R chops are kinda redundant) and produce reusable code (i.e. beyond Jupyter notebooks). Other languages are a plus.
  • You have understanding of scalable data processing technologies like Spark, Hadoop, Kafka, Apache Beam and cloud implementations like Google Dataproc, Kinesis, EMR.
  • You are a good coder and more than heard about modern software development practices of code management, code reviews, continuous testing, continuous deployment, continuous delivery - creating data insight products means writing good code.
  • Since Vogons destroyed our clunky on-prem servers (and some laptops), we’ve moved to the clouds and never looked back. We expect you are in the same ship and no stranger to the cloud consoles and CLI SDKs.
  • You are customer focused and that means that you can’t just ignore reality and dive into an interesting problem for few weeks and then come up with something brilliant that may or may not be applicable to the project. You are always in touch with the customer.
  • You have fun at work but you do other things too be it run, bike, play music, rock climb, sing, swim, ski and what not.
  • You work because you love this job (and it pays too)
  • You own a towel


The real you

There is reality too… While you will most probably not have all of the above, you would be keen and capable to close those gaps quickly.


What’s in it for you?

  • Competitive total rewards packages
  • Why Commute? Work remotely
  • Outstanding people Collaborate with the industry’s top minds
  • Learn new things. Work on various projects.
  • Substantial training and office allowances Hone your skills or learn new ones; participate in professional development days, purchase a device of your choosing and personalise your work environment  
  • Fun, fun, fun  blog during work hours; take a day off and volunteer for your favorite charity
  • Being part of a world domination plan. Make a difference.



Intrigued to see what a job is like at Pythian or check us out @Pythian and #pythianlife. Follow @PythianJobs on Twitter and @loveyourdata on Instagram!


Not the right job for you? Check out what other great jobs Pythian has open in Ottawa and around the world! Pythian Careers



  • We thank all applicants, however, only those selected for an interview will be contacted. Selected candidates will be given a technical challenge.
  • Pythian is an equal opportunity employer and welcomes applications from people with disabilities.  Accommodations are available on request for candidates taking part in all aspects of the selection process.
  • All applicants will need to fulfill the requirements necessary to obtain a background check



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