Data Scientist

GenLogs Corporation Open · verified Oct 24, 2026

Remote United States Full-time Mid-level Data Science

At a glance

Mid-level Data Science role at GenLogs Corporation. Remote, United States · full-time · no salary stated · we estimate $115,300–$175,500 across the United States.

Estimated pay

GenLogs Corporation has not published a salary for this role. The figure below is our estimate, not theirs.

$115,300 – $175,500

What the middle half of mid-level data science roles in the United States paid, among postings that did state a salary.

Worked out from 425 postings that stated pay, median $145,000. Last updated Oct 24, 2026.

RoleData Science

SeniorityMid-level

LocationUnited States

WorkplaceRemote

EmploymentFull-time

PostedDec 10, 2025 · 10mo ago

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Build machine-learning systems and examine noisy camera, OCR, detection and geospatial data for useful patterns
Design and assess methods for truck matching, location clustering, equipment labeling, OCR, and anomaly detection
Move models from early prototypes into production with engineering and data engineering teams
Turn product teams’ understanding of customer needs into modeling and analytics work
Test and refine approaches as new observations become available

What you bring

You have two to five years in data science, machine learning or software engineering
Your technical education or background is in engineering, physics, math, computer science or a related applied field
You can build or deploy models using core machine-learning methods, computer vision, geospatial analysis or related algorithms
You program confidently in Python and can work with current data and machine-learning libraries

Who this fits

This suits a technically curious problem solver who can work through ambiguous questions and messy real-world data, then collaborate with engineering, data and product colleagues. The position is remote within the United States.

From the employer

GenLogs is a transportation-technology company building the next generation of truck intelligence. Through a nationwide network of sensors and proprietary data, we deliver real-time, high-fidelity insights into freight movement for commercial supply-chain customers and public-sector agencies. Our mission is to strengthen America’s logistics backbone, combat freight fraud and cargo theft, and provide near-instantaneous visibility into commercial motor vehicle activity across major freight corridors. By operating at the intersection of edge sensing, computer vision, AI-driven analytics, and large-scale field deployment, GenLogs is transforming how transportation data is captured, secured, and commercialized.

ABOUT THE DATA TEAM

The Data Science team at GenLogs transforms raw observational data from the our sensor network into high-value intelligence used by law-enforcement agencies, regulators, ports, and private-sector freight operators. We build models, analytics, and measurement frameworks that enable vehicle detection, entity resolution, behavioral insights, fraud and theft indicators, compliance signals, and network-wide operational performance metrics. Our work sits at the center of the freight intelligence platform, shaping how billions of roadside observations become actionable information. We partner closely with Engineering and Product to deploy algorithms at scale and with Go-to-Market teams to define customer-facing analyses that drive real operational outcomes. The team blends statistical rigor, ML capability, and domain expertise to create a new standard for freight intelligence in the United States.

ABOUT THE JOB

You’re a problem solver at heart. You thrive at the intersection of engineering, math, and machine learning, and you’re motivated by questions that don’t have obvious answers. You bring a background in engineering, computer science, physics, applied math, or another hard science discipline, and you enjoy applying that technical foundation to real-world ML challenges.

You are energized by ambiguity, obsessed with understanding how complex systems behave, and capable of breaking down big problems into tractable iterations. You ask great questions, validate assumptions with data, and are relentless in your pursuit of signal over noise.

WHAT YOU’LL DO

Build machine-learning systems that power some of the most advanced logistics intelligence products in the industry
Analyze large, noisy datasets from cameras, OCR, detections, and geospatial pipelines to uncover actionable patterns
Design and evaluate algorithms for truck re-identification, geospatial clustering, equipment classification, OCR text labeling, anomaly detection, and more
Collaborate with engineering and data engineering teams to scale models from prototype to production
Work closely with product teams to deeply understand customer needs and translate them into modeling and analytics initiatives
Apply scientific thinking to continuously test, iterate, and refine approaches as new data becomes available

REQUIRED QUALIFICATIONS

2–5 years of professional experience in Data Science, Machine Learning, or Software Engineering
Technical foundation in engineering, physics, math, computer science, or related applied fields
Experience deploying or building models using:
- Machine learning fundamentals (classification, clustering, time-series, anomaly detection)
- Computer vision (OCR, object detection, embeddings)
- Geospatial data analysis (mapping, clustering, location intelligence)
- Association/sequence pattern mining, feature engineering, or algorithm development
Experience working with cloud-based data tooling (Snowflake, AWS) — not required but nice to have
Strong programming skills in Python and comfort with modern data/ML libraries (PyTorch, Pandas, Scikit-learn, etc.)
Comfort working with real-world messy datasets (sensor data, imagery, telematics, transactional freight data)

WHO WILL SUCCEED HERE

US SALARY RANGE

GenLogs establishes compensation based on role, level, experience, and location. Salary bands are benchmarked against high-growth technology companies and adjusted for market conditions. Equity grants are included in most full-time offers to ensure every team member participates in the company’s long-term value creation. A recruiter will provide a precise range during the hiring process.

BENEFITS