Viaduct

AI-powered predictive maintenance from vehicle data

Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeSloveniaNo salary listedIn-person

About the Job

Requirements

Strong machine learning and statistical analysis skills.
Comfort working side-by-side with customers.
Strong presentation skills for communicating technical concepts to non-technical audiences.
Familiarity with working on datasets that do not fit within a single machine.
Ability to work independently.
Excellent spoken and written communication skills.
A minimum of a Master of Science degree in a data science-related field and 2+ years of experience in a related field.
Proficiency in Python and SQL.
Hands-on experience with machine learning libraries such as scikit-learn, XGBoost, and MLlib.
Familiarity with deep learning libraries such as TensorFlow, Keras, and PyTorch.
Working knowledge of distributed/cloud compute platforms such as AWS, Hive, ClickHouse, and Argo Workflows.
Experience developing agentic workflows.
Experience deploying and maintaining data pipelines and data science-backed product features.

Responsibilities

Learn Viaduct’s history and mission, meet team members, set up the development environment, and understand the data pipelines, data science workflow, partners, and their needs.
Present initial deliverables internally, scope and propose product improvements, deploy improvements to machine learning/agentic pipelines, and present work at weekly team meetings.
Deploy data science-based products and services, collaborate with engineers to improve data science tooling, and present models and relevant metrics to stakeholders.
Follow security and privacy policies and procedures and Employee Handbook guidelines; participate in new-hire and annual security and privacy training; treat data security and privacy as a primary job responsibility; report discovered security incidents as bugs; obtain Security Team approval before adding third-party software to the codebase; and consider security implications during pull-request reviews.

At Viaduct, we are developing an end-to-end AI-powered machine learning platform to empower industry to build safer, more intelligent, and reliable assets. Our platform increases the accessibility and actionability of connected asset data for industry, their partners and end-customers. We are a diverse team motivated to solve the hardest problems in the asset performance management sphere.

Who You Are

You are motivated by real-world problems and enjoy working with stakeholders to solve their biggest challenges. You are excited by opportunities to deliver value by turning data science into actionable business and technology insights.

Expected Skills

Strong machine learning and statistical analysis skills
Comfort working side-by-side with customers
Strong presentation skills communicating technical concepts to non-technical audiences
Familiarity with working on datasets that don't fit within a single machine
Self-motivated and able to work independently
Excellent spoken and written communication skills
Minimum of advanced degree (M.S.) in a data science-related field and 2+ years of experience in a related field
Proficiency in Python and SQL
Hands-on experience with ML libraries (scikit-learn, xgboost, MLlib, etc.)
Familiarity with deep learning libraries (Tensorflow, Keras, PyTorch, etc.)
Working knowledge of distributed/cloud compute platforms (AWS, Hive, Clickhouse, Argo-workflows, etc.)
Developing agentic workflows
Experience deploying and maintaining data pipelines and DS-backed product features

About the Role

Day 5

Learn about Viaduct’s history and mission
Get to know every team member
Set up your development environment
Understand Viaduct’s data pipelines and data science workflow
Learn about our current partners, their biggest needs, and the gaps they're looking for us to fill

Day 30

Present your first deliverables internally
Scope-out and propose improvements to our products
Deploy improvements to our ML/Agentic pipelines
Present your work at our weekly team meetings

Day 90

Be a thought leader on the data science team
Deploy world-class DS-based products and services
Collaborate with engineers on improvements to data science tooling
Present your models and relevant metrics to stakeholders

Security and Privacy Responsibilities

Follow our policy and procedure documents related to security and privacy
Follow the guidelines in the Employee Handbook
Participate in new hire and annual training for security and privacy
Treat data security and privacy as one of your primary job responsibilities
Report Security Incidents you discover as bugs
Get approval from the Security Team before adding new 3rd party software to our codebase
Explicitly consider security implications when doing PR reviews

About the Company

Viaduct

AI-powered predictive maintenance from vehicle data

Viaduct analyzes connected vehicle data through a cloud platform powered by its patented TSI Engine. It uses AI to automatically process large data volumes to identify patterns and predict issues with vehicle components. Its applications include predictive maintenance, driver identification, and driver safety scoring for automotive manufacturers and other automotive ecosystem players. Practically, the TSI Engine ingests telematics and vehicle data, runs machine learning models in the cloud, and outputs insights and risk assessments that help schedule maintenance and improve safety. Viaduct differentiates itself with a patented engine and a cloud-based data analytics platform focused on connected vehicles, combining predictive maintenance with driver-related analytics. The company’s goal is to improve vehicle reliability and safety by turning data into actionable insights through machine learning and data analytics.

Company size: 51-200
Company stage: Acquired
Total funding: $21M
Headquarters: Menlo Park, CA
Founded: 2019

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