Math Related Jobs — Remote, Contract, and Full-time on Rex.zone

math related jobs are roles where mathematical reasoning, quantitative analysis, and statistical modeling drive decisions, products, and AI systems. On Rex.zone, employers post math related jobs that connect directly to AI/ML training workflows such as data labeling, RLHF (Reinforcement Learning from Human Feedback), prompt evaluation, and large language model evaluation. Whether you’re targeting NLP, computer vision, optimization, or risk modeling, Rex.zone helps you discover remote, contract, freelance, full-time, entry-level, and senior opportunities at AI labs, tech startups, BPOs, and annotation vendors. Apply once, showcase your skills, and match with teams focused on model performance improvement, training data quality, and production-grade analytics.

About math related jobs: entities, roles, and AI workflows

math related jobs span data science, machine learning, operations research, actuarial science, quantitative finance, and applied research. In modern AI companies, these roles intersect with LLM training pipelines, computer vision annotation, named entity recognition (NER), content safety labeling, and QA evaluation. Mathematicians and quantitative professionals design experiments, optimize loss functions, and validate models with statistically principled methods. On Rex.zone, postings explicitly map responsibilities to steps such as problem framing, data labeling and augmentation, feature engineering, model training and evaluation, RLHF protocols, and deployment monitoring. This alignment ensures every candidate understands how their mathematics expertise improves training data quality, annotation guidelines compliance, and overall model performance improvement.

Popular titles and subdomains you’ll find on Rex.zone

Explore a broad, searchable catalog of math related jobs that includes classic and emerging titles across AI and analytics. Hiring teams label each listing with domain tags to improve discovery and n-gram relevance, helping candidates filter by tech stacks, industries, and workflow responsibilities.

Work formats and seniority levels

Rex.zone aggregates math related jobs across remote, contract, freelance, and full-time formats, spanning entry-level to senior leadership. Entry-level roles emphasize statistical literacy, SQL, Python, and structured mentorship. Mid-level professionals own modeling roadmaps, collaborate with data engineering on pipelines, and lead model evaluation. Senior staff and principals influence portfolio strategy, mentor teams, and drive cross-functional results in AI labs and tech startups, while consulting arrangements with BPOs and annotation vendors focus on annotation quality systems, evaluation frameworks, and scalable guidelines.

Key responsibilities aligned to AI and analytics pipelines

While responsibilities vary by employer type, math related jobs usually share pipeline-aligned tasks with measurable outcomes. Candidates should expect to work from problem formulation to post-deployment monitoring and business communication. The following responsibilities reflect common patterns across NLP, computer vision, and structured analytics.

Core skills and qualifications

Strong mathematical foundations combined with practical tooling distinguish competitive applicants for math related jobs. Employers commonly seek candidates who demonstrate fluency in theory, implementation, and cross-functional communication.

Where math meets LLM training pipelines

In LLM programs, math related jobs often own the design of evaluation metrics, uncertainty quantification, and sample-efficient labeling strategies. Teams coordinate with data labeling leads to build high-quality datasets and with RLHF specialists to convert human preferences into reward functions. Mathematicians establish inter-rater reliability, optimize sample allocation, and monitor drift with statistical process control. They prototype safety taxonomies for content safety labeling, develop stratified sampling for prompt evaluation, and connect metrics directly to model performance improvement targets, ensuring decisions remain grounded in rigor.

Sectors and employers actively hiring

Rex.zone hosts math related jobs from diverse employers who rely on mathematical rigor to drive outcomes across product, research, and operations.

Compensation, progression, and impact

Compensation for math related jobs reflects domain depth, impact, and geography. Remote roles with scarce skills—optimization at scale, probabilistic programming, or safety evaluation—command premiums. Career progression spans IC tracks (Senior, Staff, Principal) and management. Professionals amplify impact by owning end-to-end analytics: defining metrics, improving training data quality, tying model performance to user outcomes, and validating effects with robust A/B testing and causal inference. Rex.zone listings include salary ranges, equity or bonus structures, and benefits transparency whenever provided by employers.

How to apply on Rex.zone

Applying to math related jobs on Rex.zone is streamlined and portfolio-first. Complete a single profile, attach key projects, and enable role alerts for your focus domains (NLP, CV, OR, econometrics). Use saved filters for remote, contract, freelance, and full-time openings, and track application status in one dashboard.

Interview preparation and portfolio signals

To stand out for math related jobs, emphasize reproducible work and principled methodology. Recruiters respond to candidates who link math choices to production constraints and user outcomes.

Tools, platforms, and infrastructure

Many math related jobs require fluency with modern data and ML stacks. Rex.zone postings specify tools to set expectations and improve candidate-job matching.

Early-career pathways and upskilling

Entry-level candidates for math related jobs can break in via internships, research assistant roles, or analyst tracks with strong mentorship. Focus on foundational statistics, SQL, Python, and one domain specialization—such as NLP tokenization and embeddings, computer vision data augmentation, or operations research with linear programming. Certifications and practical coursework matter less than a portfolio demonstrating end-to-end execution: data wrangling, modeling, evaluation, and error analysis tied to business goals. Rex.zone highlights junior-friendly roles and apprenticeship-style postings with clear growth ladders.

Senior impact: from modeling to strategy

Senior professionals in math related jobs define modeling roadmaps, influence data collection, and build evaluation frameworks that scale. They mentor teams on sampling strategies, champion annotation guidelines compliance, and create dashboards that tie model performance improvement to product KPIs. They also collaborate with security, legal, and policy to manage privacy, fairness, and risk. Rex.zone’s senior listings emphasize scope, stakeholder complexity, and measurable outcomes so applicants can assess fit and impact.

Search modifiers and how to filter effectively

Use precise search modifiers on Rex.zone to surface the best math related jobs quickly. Combine role, seniority, domain, and employment type. Save filters to receive curated alerts.

Call to action

Ready to find high-impact math related jobs? Create your Rex.zone profile, set your domain preferences, and apply to roles that match your strengths. Whether you’re optimizing training data quality, leading RLHF evaluations, or delivering production-grade forecasting, Rex.zone connects you with employers that value mathematical rigor and measurable outcomes.

Frequently Asked Questions

Q: What are math related jobs in the context of AI and analytics?
They are roles where mathematics drives decisions and systems: data science, ML engineering, operations research, actuarial modeling, quantitative research, and evaluation-focused positions (RLHF, prompt evaluation, annotation QA). These roles improve training data quality, design robust metrics, and link model performance improvement to user impact.
Q: Which industries hire for math related jobs on Rex.zone?
AI labs, tech startups, BPOs and annotation vendors, finance, healthcare, logistics, manufacturing, and edtech. Listings clarify domain tags such as NLP, computer vision, content safety, and LLM training.
Q: Are remote and contract options available?
Yes. Rex.zone features remote, contract, freelance, and full-time postings. You can filter by employment type, seniority, and domain to find entry-level or senior opportunities.
Q: How do math skills integrate with LLM training pipelines?
Mathematicians and data scientists design evaluation metrics, sampling plans, and human-in-the-loop protocols like RLHF. They ensure annotation guidelines compliance, stabilize inter-rater reliability, and connect large language model evaluation to business KPIs.
Q: What skills should I prioritize to be competitive?
Strong probability and statistics, optimization, Python/R/SQL, experiment design, and communication. For domain roles: transformers for NLP, augmentation and detection for CV, and linear programming or MIP for operations research.
Q: How do I stand out with limited experience?
Publish reproducible projects with clear objectives, metrics, and trade-offs. Include a small RLHF or evaluation project, show annotation rubric design, and provide experiment tracking artifacts (MLflow runs, seeds, versioned data).
Q: Do postings include salary ranges?
Many do. Rex.zone encourages employers to share ranges, benefits, and leveling frameworks. Candidates can filter for listings with transparent compensation.
Q: What types of employers use Rex.zone for evaluation-focused roles?
Teams running large-scale data labeling and model evaluation, including BPOs, annotation vendors, and AI labs. Roles include QA evaluation leads, prompt evaluators, and RLHF specialists who collaborate with research and product teams.
Q: How quickly can I apply to multiple roles?
With a Rex.zone profile, you can apply to several math related jobs in minutes, reuse materials, and enable employer discovery for matched roles.

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