Lead Data Scientist - Canada - Contract to Perm

About Very

Very is a fully remote IoT technology firm led by expert problem-solvers to create efficient, scalable solutions that move commercial, industrial, and consumer IoT projects from pilot to production in record time. 

We’ve built a collaborative, tight-knit team that thrives, whether we’re hanging out in person or coordinating work across time zones. The results show that we’re doing something right — as we’ve won numerous workplace awards over the years. Most recently in 2021 we were certified as a Great Place to Work, and in 2022 we were listed again in Parity.org’s list of Best Companies for Women to Advance.
 

We believe that everything we build — and the people we build it with — has the potential to change the world. Our client list includes numerous well-known brands determined to leverage the power of IoT to drive material outcomes — such as Vizio, Peloton, Clear, iHeart Radio and Fellowes. Our goal, for each and every client we partner with, is to create high-value solutions through a collaborative and user-centered process. #LI-Remote

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About This Role

As a Lead Data Scientist at Very, you will work with our Software, Hardware, and Product Design teams to build full-service solutions for our clients. We focus on building end-to-end hardware and software solutions that meet our client's business needs, and reliable algorithms and machine learning systems are often a part of our offering. An ideal candidate will display technical expertise in algorithms, machine learning and data science, strong communication skills, and the ability to present ideas and results to audiences ranging in technical depth. Candidates should also have experience translating business problems into analytical solutions, working in interdisciplinary teams, and building models for production systems.

A Lead at Very is an individual who operates with the highest degree of knowledge and accountability for the delivery of services to our customers.  They provide excellent technical leadership and delivery skills, as it pertains to complex, multi-faceted projects at Very. They have a strong executive presence, which gives major client stakeholders the confidence that we will deliver, and gives our team the confidence and accountability to do so.  

As a client services organization, travel may be required up to 10% of the time.

What You’ll Be Working On

At Very, there is a never-ending supply of variety to the projects we work on. However, it is critical to note that almost all of these projects are production systems. As such, the only consistent research component of this position will revolve around establishing a pattern of delivery that allows the team to implement full-scale applications leveraging data science in a fast, predictable manner. 

Lead engineers also regularly serve as a sales solutions engineer and are entrusted by the commercial team to be their main technical partner for closing high value contracts. They will travel onsite with clients, fine tune deliverables/staffing plans, and otherwise do what it takes to close these contracts with terms that are conducive to successful delivery.

Responsibilities

• Classical statistical analysis and signal processing
• Prediction, state classification and anomaly detection on multivariate time series data
• Regression and classification using a variety of classical and deep learning methods
• Machine vision and automated speech recognition
• Application of transformer architectures including composite and agentic AI
• Deployment and monitoring of ML workflows into both the cloud (AWS & Azure) and the edge (Nordic, NXP, NVIDIA & Intel) 
• MLOps infrastructure and best practices
• Planning, implementing and communicating the results of algorithm field testing
• Walking clients through the data science journey and partnering with design to build effective visualizations and metrics for web and mobile applications
• Coach and mentor other engineers
• Participate in recruiting of candidates and improvement of the overall interview process
• Support sales and pre-sales engineering work to ensure Very <> Client fit

Our data science contracts typically involve building a full greenfield IoT data pipeline and MLOps lifecycles. This extends from the IoT sensors and/or actuators, through any local networks, into the cloud, to the user interface and back again. In the context of the data science, we typically leverage:

• Git, GitHub, GitHub Actions (CI/CD), pytest (TDD)
• The standard SciPy Stack (Numpy, SciPy, Pandas, Scikit-Learn, Matplotlib)
• Standard Python related data science tools such as SQL/Postgres, Docker, MLFlow, PySpark, PyTorch, TensorFlow and LangChain
• Jupyter notebooks for prototyping
• Cloud architecture and resources for production systems

• AWS: Lambda, ECS, RDS, DynamoDB, IoT Core, Greengrass, Sagemaker, Bedrock
• Azure: Functions, Container Registry, SQL Database, Machine Learning, IoT Hub
• 3rd party: Ultralytics, TimescaleDB, Datadog, Peridio
• IaC: Terraform

As an IoT technology company our data science pipelines include “Things”. This will require you to build pipelines and deploy analytical models to hardware on the edge in addition to the cloud. This requires a deep collaboration with the design, software and hardware teams in the following environments:

• Yocto, Linux and macOS development environments
• Elixir, Phoenix, and Nerves

• Embedded C and other lower level languages such as Rust
• CI/CD including hardware and end-to-end testing and verification
• Development Single-Board Computers such as RPi

We value well-tested, reusable code and expect our engineers to be as good of practitioners as they are leaders and teachers.

Required Qualifications

Unfortunately, applicants who do not meet these criteria will not be considered.

Experience:

• Master’s degree in Data Science related field
• 7+ years of related experience
• Deployed statistical, ML or other analytical models to production
• Lead teams with hardware and software engineers
• Performed real-time signal processing and lead teams that did so
• Worked directly with clients and partnered with sales and client success teams to secure new work 
• Partnered with client success and senior executives ensure the success of current and future projects 
• Strong written and spoken communication skills in English 
• Proficient in Agile development and breaking solutions into “thin vertical slices” of work 
• Guiding interdisciplinary team to successfully estimate and execute these slices   
• Experience developing and managing AWS workflows
• Expert-level Python development skills related to Data Science
• Automated testing, code coverage, model building & evaluation
• SciPy Stack, Scikit-learn, Tensorflow or PyTorch
• GitHub CI/CD best practices 
• Experience developing, compiling and deploying C, C++ or Embedded C software
• Proficient developing in Linux including and light administration

Nice-to-have

• 10+ years of related experience including with connected devices
• Proficient in embedded real-time signal processing
• AWS Professional level certification
• Familiarity with Elixir, Phoenix, and Nerves
• Hands-on experience with Single-Board Computers such as RPi

Skills:

In addition to experience, these are the critical skills we look for in all technical roles, and how they should be demonstrated at the Lead level.

• Communicates Effectively: Demonstrates expert-level communication skills. Communicates to inform, engage and inspire. Negotiates for positive outcomes with clients on complex projects.
• Influences broad audiences and creates compelling narratives around their ideas and why they are important.
• Demonstrates an expert level of knowledge and experience and as a result instills confidence in technical ability by team and clients.  
• Takes calculated risks and shows a commitment to innovation that improves the business and tech community.
• Accurately estimates full scale engagements for Statements of Work, as part of the sales process. 
• Leads people through our toughest program scenarios toward successful outcomes. Provides quick redirection when needed.