Principal Data Scientist - Canada

Key Skills

AWS, Azure, C++, CircleCI, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, Deep Learning, Docker, Effective communication skills, Git, Google Cloud Platform (GCP), Jupyter Notebook, Leadership Skill, Machine learning techniques, MLOps tools, NumPy, Pandas, Python Programming, PyTorch, Scikit-learn, SciPy, Signal processing, SQL, TensorFlow

Job Description

About This Role

As a Principal 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 Principal at Very is an individual who operates with the highest degree of knowledge and accountability for delivering 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. 

Principal 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.

A principal engineer may be designated as the Chief Engineer (CE) for several high complexity and high value projects. The CE is the leader of the project team. Despite the title of “Engineer” – the Chief Engineer should not participate in the implementation of tickets. Their responsibility is to ensure that the remainder of the team is able to fulfill their responsibilities, set and maintain the technical direction of the program and when necessary, escalate the project into triage mode and effectively partner with the rest of the project leadership team to get the account back on track.

As a principal data scientist, you will be expected to not only understand the following analytical approaches but also be able to guide others in their implementation and set new standards for the practice.

- Predictive modeling and anomaly detection on multivariate time series data

- State classification and prediction for geospatial time series data

- Regression and classification using a variety of deep learning and ensemble tree-based methods

- Clustering and segmentation

- Dimensionality reduction or latent space representation

- Classical statistical analysis and signal processing

- MLOps infrastructure and best practices

Our Current Tooling

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)

- SQL/Postgres, Docker, MLFlow, PySpark, PyTorch and TensorFlow

- Jupyter notebooks for prototyping

- Cloud architecture and resources for production systems

-- AWS: Lambda, ECR/ECS, RDS, API Gateway, Batch, Sagemaker, IoT Core

-- Azure: Functions, Container Registry, SQL Database, API Management, Machine Learning, IoT Hub

-- GCP: ML Engine, BigQuery, Cloud Storage, Compute Engine, Looker Studio, Functions

-- 3rd party: TimescaleDB, Datadog, 

-- IaC: Serverless or 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:

- 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

Qualifications

Required

Required

- 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

- Mastery in analytical framing

-- Breaking down solutions into “thin vertical slices” of work 

-- Guiding interdisciplinary team to successfully estimate and execute these slices

- Deep understanding of all four types analytics (Descriptive, Diagnostic, Predictive & Prescriptive)

-- Translating desired client outcomes to the appropriate type

-- Understanding the data requirements and techniques to achieve each type

- Experience using AWS, GCP and Azure 

- Expert-level Python development skills related to Data Science

-- Object-Oriented Programming

-- Automated testing, code coverage, model building & evaluation

-- SciPy Stack, Scikit-learn, Tensorflow or PyTorch

-- GitHub CI/CD best practices 

- Experience developing in, compiling and deploying low level software; C++, Embedded C or Rust preferred

- 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

Responsibilities

-- Work with stakeholders (clients, sales, engineers & designers) to define Statements Of Work (SOW)

-- Communicate how data science can deliver value to the client

-- Estimate quantity of work required to unlock this value

-- Identify related assumptions, risks and dependencies 

- Take ownership of the data science components and related systems to ensure project success

-- Architect, build and deploy reliable end-to-end data and ML pipelines into production

-- Ensure the highest level of testing across the full data pipeline and operating envelope

-- Execute and document all algorithm verification testing for certification

-- Build and nurture strong relationships with clients, understand their perspective and walk them through the data science value chain

-- Facilitate complex conversations to achieve alignment to drive positive outcomes

- Continue to expand and evolve the Data Science (DS) practice at Very

-- Provide technical guidance to DS and non-DS team members

-- Pairs with mid team members to develop their skills and deliver on projects 

-- Continually learn, share and refine your DS skills and knowledge

-- Establish and enact DataOps and MLOps best practices 

- Take on the responsibility of Technical Lead on complex multi-disciplinary projects

- - Build reliable product roadmaps with technical implementation strategies

- - Monitor and optimize the technical implementation and coordination of the project

- - Identify and mitigate risks and seek assistance when required 

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

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 Principal 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.

Compensation

Base Compensation

Between USD $153,750 and $168,750 per year, commiserate with experience.

Variable Compensation

Up to 15% of your base compensation in the first year

We also offer world-class perks:

- Extended Health Care Insurance (Medical, Dental, Vision)

- Paid Parental Leave

- Life Insurance / AD+D

- Registered Retirement Service Plan RRSP = 25% / Match- $1 CAD for every $4 CAD contributed.

- USD $600/yr Home Office Stipend to use towards your home office/workstation.

- $2,500 yearly stipend for continuous education upon one year of employment.

- USD $150/mo Monthly Communications Stipend (Can be used towards Cell Phone Data Plan, WiFi Plan, VOIP, VPN)

- Annual company trip, all expenses paid.

- Loaned MacBook Pro (Provided)

Why Work for Very

You are more than your job title. At Very, we prioritize talent development and professional growth with a human-first approach that caters to the unique goals each individual brings to the team. 

Our core value, Invest in Our People, looks like collaborating with a cohort of talented people on a mission to get better every single day. It feels like working for a company that invests in you. And it means finding alignment with your career goals to get you where you want to be.

How do we bring our priorities to life? Of course we offer the typical world-class perks you would expect. Additionally, as a remote-first company (since 2011), we provide stipends for home office, telephone, and internet. Professional development funds and generous parental leave are also some of the benefits you can expect.

But a healthy company culture isn't just about perks. It's about creating an environment where our employees can thrive. Our work is fueled by smart, creative people whose lives are enriched by our experiences together. We learn together, we grow together, and we play together. Despite working across more than half a dozen countries, our teams connect regularly for work and for fun - on Slack, Zoom, and during an annual retreat. We’ve been remote-first from the beginning, so we know well what it takes to maintain a strong culture. #LI-Remote

IMPORTANT: 

1. This job is to work for a US company. An advanced level of English is a must. Please refrain from applying if this is not your case. 

1. We currently don't offer work visa sponsorship. Do not apply if you require it to stay in Canada.

1. This job is remote but if you’re located in the province of Quebec, we cannot accept your application at this time. This is due to Quebec’s labor laws.

1. The region/country on the post's title is not related to the location of the clients we serve. It's a reference to the residence location of the applicant. All of Very's clients are North America-based.

1. Delivery team members may be required to travel up to 10% of the time. As a client services organization, this is expected.