Data Scientist

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