Data Scientist

genlogs-corporation; United States; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Healthcare

Unlimited PTO

Parental leave

Professional development budget

Travel reimbursement

401(k)

Job summary

GenLogs is shaping the next generation of truck intelligence by turning sensor data into actionable insights for freight operators and regulators. The Data Science team builds models and analytics to detect patterns, track vehicles, and deliver compliant, scalable solutions.

You will work at the intersection of engineering, math, and ML, tackling ambiguous problems with data-driven methods and collaborating across product and engineering teams to deliver impactful results.

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; 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)

Responsibilities

• 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

Skills

Data Science

Machine Learning

Software Engineering

Python

AWS

Computer Vision

Geospatial Analysis

Tools

PyTorch

Pandas

Scikit-learn

OpenCV

Job description

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

You will love this role if you are:

• Relentlessly curious — you ask "why?" repeatedly until you reach the root


• Technically fearless — not afraid to dive into large datasets, new ML techniques, or unfamiliar codebases


• Impact-driven — you want your models to power real, high-stakes decisions in a massive industry


• Comfortable with ambiguity — our data is large, messy, and evolving, and that excites you


• Collaborative — you enjoy working with engineers, data teams, and product stakeholders to deliver real customer value

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

Healthcare (US based only)

• Employer-covered comprehensive medical, dental, and vision plans


• Employer contribution towards premiums of optional higher-end plans

Time Off

• Unlimited PTO


• Sick leave


• Company holidays (GenLogs observes all US Government holidays)


• Flexible leave for caregiving and medical needs

Family Support

• Paid parental leave

Professional Development

• Budget availability for approved professional development courses, certifications, and training

Travel Support

• 100% travel reimbursement for all approved company travel and spending

Retirement Savings

• 401(k) plan (US based employees)

A recruiter can provide more detail about the specific compensation and benefits associated with this role.