Data Scientist II

Arrivelogistics; Chicago (IL); On-site; USD 90,000 - 115,000; Full time

Benefits offered by this job

Comprehensive benefits package

Matching 401(k) program

Employee Resource Groups

Casual dress code

Work in downtown Chicago

Fitness facility

Employee Assistance Program

Paid holidays and vacation

100% paid parental leave

Relocation assistance

Job summary

Arrive Logistics is searching for a Data Scientist II to enhance machine learning systems that drive operational value. The role emphasizes experience in NLP and LLM systems, requiring strong statistical and Python skills.

You will contribute to full lifecycle ML systems, focusing on text and language applications. The ideal candidate should have a quantitative degree and hands-on experience, coupled with excellent communication skills.

Qualifications

• 2–4 years of applied ML or data science experience, or equivalent practical experience.
• Hands-on experience with NLP or LLM-based systems.
• Strong written communication skills to document systems.

Responsibilities

• Develop and iterate on NLP and LLM-based systems.
• Build measurement frameworks to evaluate performance.
• Document work clearly and maintain knowledge artifacts.

Skills

NLP Systems

Machine Learning

Python

SQL

Statistical Methods

Data Annotation

Education

Bachelor’s or Master’s in quantitative field

Tools

Hugging Face Transformers

LangChain

LangSmith

Job description

Who We Are

Arrive Logistics is a leading transportation and technology company in North America with plans to grow significantly year over year. Our success is a testament to our remarkable team and what we’re building together. We’re committed to providing employees with a meaningful work experience and have established an award‑winning culture that supports personal and career development in a fun, casual, and collaborative environment.

Position Overview

The Data Scientist II will work closely with Data Science, Product, and Engineering to build and improve ML and AI systems that drive operational value. This role is a great fit for a hands‑on practitioner with applied experience in NLP and LLM‑based systems who is ready to take on meaningful technical ownership. You'll contribute to the full lifecycle of production ML systems — from evaluation and measurement through development, deployment, and iteration — with a particular focus on text and language‑based applications. The ideal candidate is comfortable operating in ambiguous problem spaces, can translate loosely defined business needs into concrete technical approaches, and communicates findings clearly to both technical and non‑technical audiences.

Responsibilities

• Develop, evaluate, and iterate on NLP and LLM‑based systems, including text classification, information extraction, and context retrieval pipelines.
• Build measurement and evaluation frameworks — both offline and online — to assess where and why systems are underperforming and quantify the impact of improvements.
• Develop golden test datasets and define methodologies for creating and maintaining them over time, including designing annotation guidelines and ensuring label quality.
• Evaluate and apply the appropriate approach for language tasks — whether prompt engineering, fine‑tuning, or classical NLP methods — including modern retrieval and RAG architectures and LLM evaluation methodologies, based on the problem and available data.
• Perform structured analysis of system performance to surface failure modes, data gaps, and high‑value areas for investment, applying sound statistical reasoning to evaluation results.
• Partner with engineers to support deployment, integration, and monitoring of ML and AI systems in production.
• Contribute to standards and best practices around deploying, evaluating, and monitoring text and language‑based ML systems.
• Document work clearly and maintain knowledge artifacts that make systems understandable and maintainable over time.
• Collaborate with senior data scientists and cross‑functional partners to translate business needs into well‑scoped technical solutions, including communicating findings and recommendations to non‑technical stakeholders.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field (computer science, statistics, linguistics, or related) and 2–4 years of applied ML or data science experience, or equivalent practical experience.
• Hands‑on experience building or improving NLP or LLM‑based systems in applied settings.
• Familiarity with text classification, information extraction, or other NLP tasks — and an understanding of where these systems fail.
• Experience with both prompt engineering and fine‑tuning approaches for language tasks, with the judgment to know when to apply each.
• Familiarity with modern retrieval strategies and RAG architectures and how they affect LLM system performance.
• Experience with Hugging Face Transformers for text classification or related NLP tasks.
• Experience contributing to evaluation frameworks, test sets, or performance diagnostics for ML systems, including comfort with statistical methods for measuring model performance.
• Proficiency in Python and SQL, and comfort working with structured and unstructured data.
• Ability to operate effectively in ambiguous problem spaces — scoping technical approaches when requirements are not fully defined.
• Strong written communication skills; able to document systems and findings clearly and present recommendations to non‑technical stakeholders.
• Experience designing data annotation workflows, labeling guidelines, or label quality processes is a plus.
• Experience with model deployment, monitoring, or production ML workflows is a plus.
• Familiarity with LangChain and LangSmith or similar LLM orchestration and observability tooling is a plus.
• Transportation or logistics industry experience is a plus.

Benefits

• Comprehensive benefits package, including medical, dental, vision, life, disability, and supplemental coverage.
• Matching 401(k) program.
• Employee Resource Groups and learning opportunities.
• Office wide engagement activities, team events, and casual dress code.
• Work in the heart of downtown Chicago, IL.
• Fitness facility with Peloton bikes, equipment, and personal training options.
• Employee Assistance Program with free counseling sessions.
• Paid holidays, vacation time, and wellness days.
• 100% paid parental leave.
• Referral Program.
• Relocation assistance for non‑local candidates.