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.

ⓘ View potential timezone restrictions

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.

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.

Our Current Tooling

Our 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 data science, we typically leverage the following.

Git, GitHub, CircleCI or GitHub Actions (CI/CD), pytest (TDD)
The standard SciPy Stack (Numpy, SciPy, Pandas, Scikit-Learn, Matplotlib)
Tools such as SQL/Postgres, Docker, MLFlow, PySpark, PyTorch, TensorFlow and LangChain
Jupyter notebooks for prototyping

Often the data pipeline extends to the cloud where we leverage the following cloud resources.

AWS: Lambda, ECR/ECS, RDS, DynamoDB, IoT Core, Greengrass, Sagemaker, Bedrock
Azure: Functions, Container Registry/Instances, SQL Database, Machine Learning, IoT Hub
3rd party: Ultralytics, TimescaleDB, Datadog, Peridio
Terraform for Infrastructure-as-Code

On our full-service builds, we often reach for the following tools. Experience with them is not required, but any familiarity with these tools is a plus. Our build teams operate with a very high degree of collaboration, so you will definitely have run-ins with the following stacks throughout your time here.

Python web development frameworks (Django, Flask)
React & React Native, Swift

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.

Responsibilities

Work with stakeholders (clients, sales, engineers & designers) to define Statements of Work (SoW)

Communicate how Very can deliver value to the client
Estimate quantity of work required to unlock this value for complex, multi-disciplinary projects
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 strong relationships with clients and understand their perspective
Guide clients through the data science value chain
Facilitate complex conversations to achieve alignment to drive positive outcomes

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

Provide technical guidance to DS and non-DS team members
Pairs with mid and senior 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

Required Qualifications

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

Experience:

Master’s degree in Data Science related field
5+ years of related experience
Deployed statistical, ML or other analytical models to production on AWS
Performed real-time signal processing
Lead teams with hardware and software engineers
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
Expert-level Python development skills related to Data Science including SciPy Stack, Scikit-learn, Tensorflow or PyTorch
Automated testing, code coverage, model building & evaluation
GitHub CI/CD best practices including GitHub Actions and Terraform or CloudFormation
Experience developing, compiling and deploying C, C++ or Embedded C software
Proficient developing in Linux including and light administration

Nice-to-have

7+ years of related experience including with connected devices
Proficient in embedded real-time signal processing
Machine vision and automated speech recognition
Deployment and monitoring of ML workflows to Nordic, NXP, NVIDIA or Intel hardware at the edge
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.

Compensation

Between $150,000 and $175,000 per year, commensurate with experience.

This role is fully remote but must be located in the lower 48 states of the US.

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