About the opportunity

We are looking for a Data Scientist who will turn data into insights and build models that drive meaningful business outcomes. You will work closely with cross-functional stakeholders to understand problems, design analytical solutions, and deploy data products that scale.

What to expect?

• Collect, clean, and analyze structured and unstructured data.
• Develop predictive models, statistical analyses, and machine learning algorithms.
• Build dashboards, reports, and data visualizations to communicate insights.
• Collaborate with engineering to deploy models into production environments.
• Perform exploratory data analysis (EDA) to identify trends and opportunities.
• Conduct A/B testing and design experiments to measure feature performance.
• Document methodologies and ensure reproducibility of analytical work.
• Contribute to end-to-end machine learning workflows, including model training,  validation, and deployment, working with established tools and patterns and with support from engineering.
• Monitor model performance and data quality, and update models as needed.

What do you need to be successful?

Required

• Bachelor’s or Master’s in Data Science, Computer Science, Statistics, Mathematics, or related field.
• Strong proficiency in Python (pandas, scikit-learn, NumPy).
• Experience using SQL to work with analytical databases and data warehouses.
• Solid understanding of statistical modeling, model evaluation, and experimental methods.
• Familiarity with machine learning techniques (regression, classification, clustering, etc.).
• Hands-on experience building and running machine learning models in production or production-like environments.
• Experience building dashboards with tools like Tableau, or similar.
• Strong analytical and problem-solving skills.
• Ability to balance analytical rigor with practical delivery.
• Excellent communication skills with the ability to translate data insights into business actions.

Preferred    

• Familiarity with workflow orchestration or model lifecycle tools (e.g., Airflow, MLflow) at a practical, working level.
• Implement practical model deployment approaches (e.g., batch inference, scheduled retraining) using existing team tools and patterns.
• Experience with cloud platforms (AWS, or similar).
• Knowledge of ML Ops tools (MLflow, Airflow, or similar).
• Exposure to big data technologies (Redshift, Snowflake).
• Experience working in agile environments.

What's in it for you?

• Join an ambitious tech company reshaping the way people build digital experiences
• Full-time employees receive Stock Options for the opportunity to share in the success of our company
• Comprehensive healthcare package covering 100% of monthly health premiums for employees and 85% of costs for your dependents. 
• Fertility and family building benefits, including a lifetime reimbursable wallet to support your growing family.
• We value Work-Life balance and You Time! A generous amount of paid time off, including vacation days, sick days, compassion days for loss,  education days, and volunteer days
• Company paid parental leave to care for and focus on your growing family 
• Use your personal annual education budget to improve your skills and grow in your career
• Enjoy a full range of virtual and in-person events, including workshops, guest speakers, and fun team activities, supporting learning and networking exchange beyond the usual work duties 
• An annual wellbeing stipend to care for your physical, financial, or emotional health
• A monthly communication stipend and phone hardware upgrade reimbursement.
• New hire office equipment stipend for hybrid or distributed employees. Get the gear you need to work at your best.

This role will need to be conducted in a state in which we are currently registered to do business. In addition, this position is not eligible for visa sponsorship. Applicants must be authorized to work without the need for visa sponsorship by the start date of employment.

This position is eligible for equity awards in accordance with the terms of Contentful’s equity plans.

The application deadline is 05/21/2026

Colorado Salary Statement: The salary range displayed is specifically for those potential hires who will work or reside in the state of Colorado if selected for the role. Any offered salary is determined based on internal equity, internal salary ranges, market data/ranges, applicant's skills and prior relevant experience, certain degrees and certifications (e.g. JD/technology), for example.

Colorado Salary: $136,000-$184,000

Small business owners trust Gusto with something fundamental: making sure their people get paid, on time, every time. As a Principal Data Scientist on the Payments team, you'll sit at the intersection of financial infrastructure and data science — translating the complexity of a high-scale payments ecosystem into the insights and models that shape how we build, operate, and improve our payments products. 

In this role you will work closely with our Product, Engineering, Design, Finance, and other Data teams to become an expert in the data for your domain, define and track metrics that help us understand our business performance, and dive deep into our payments data to deliver insights and answer questions. You’ll also integrate AI-assisted practices to accelerate analysis, enhance rigor, and expand the reach of insights across Gusto. 

This is a role for someone who's equally comfortable diving into ledger-level transaction data and standing in front of a payments engineering team to influence architecture decisions. If you want your work to directly protect and improve the financial lives of hundreds of thousands of small businesses, this is the role.

Here’s what you’ll do day-to-day:

• Own payments intelligence end-to-end: Design and maintain measurement frameworks for payment success rates, failure root causes, retry strategies, and settlement timing — becoming the authoritative source of truth for payments health across the org.
• Partner with payments engineering: Embed with backend engineering teams to understand infrastructure constraints and data availability, translate that knowledge into well-scoped experiments, and influence roadmap prioritization with data-backed recommendations.
• Drive experimentation at scale: Design and analyze A/B tests and quasi-experiments across payment flows — including retry logic, routing decisions, and failure recovery — ensuring statistical rigor even in low-conversion, high-variance payment environments.
• Build predictive models: Develop and deploy models for payment failure prediction, risk scoring, and anomaly detection that operate at Gusto's transaction volume, partnering with Machine Learning Engineers and Product Engineers on productionization and monitoring.
• Build AI-native data products: Go beyond using AI to go faster; build data products and automated workflows with AI as a core component. Know what "good" looks like for a clustering model or automated workflow, when to trust the output, when to challenge it, and how to build guardrails that let the team scale AI use responsibly in a regulated financial context.
• Own the business narrative: Be the person payments product and engineering leadership calls before an exec review, not after. Comfortable defending methodology on ARR projections, CX attribution, and cost savings in a room with skeptics. Translate nuanced statistical results and model outputs into clear, actionable narratives for payments engineers, product managers, finance partners, and executive leadership.

Here’s what we're looking for:

• 10+ years of experience in Data Science or a closely related quantitative role at a product-focused software company, with meaningful exposure to payments, fintech, or financial infrastructure.
• Deep payments domain knowledge: Hands-on experience with payments infrastructure: ACH, card networks, bank integrations, settlement flows, or equivalent, with a strong intuition for how backend systems shape data availability and quality.
• Strong SQL and Python skills, with experience querying large-scale transactional datasets and building reproducible analytical pipelines.
• Proven experimentation and causal inference expertise: Ability to design rigorous experiments in challenging payment contexts (rare events, high variance, non-stationarity) and communicate trade-offs clearly.
• AI-native mindset: Has built data products and analytical workflows with AI as a core component, not just used AI to go faster. Knows what "good" looks like for a clustering model or automated workflow, when to trust the output, when to challenge it, and how to build guardrails that scale AI use responsibly in a financial context.
• Cross-functional influence: Track record of collaborating with and influencing backend engineers and technical stakeholders, not just product and business partners.

Our cash compensation amount for this role is targeted at $184,000/yr - $210,000/yr in Denver, and $217,000/yr - $250,000 for San Francisco and New York. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

About the Opportunity

We’re Cleerly – a healthcare company based in Denver, Colorado and New York, New York that’s revolutionizing how heart disease is diagnosed, treated, and tracked.  We were founded in 2017 by one of the world’s leading cardiologists and are a growing team of world-class engineering, operations, medical affairs, marketing, and sales leaders. We raised $223M in Series C funding in 2022 which will enable rapid growth and continued support of our mission.

Cleerly is creating a new standard of care for heart disease through value-based, AI-driven precision diagnostic solutions with the goal of helping prevent heart attacks. Our technology goes beyond traditional measures of heart disease by enabling comprehensive quantification and characterization of atherosclerosis, or plaque buildup, in each of the heart arteries.  Cleerly’s solutions are supported by more than a decade of performing some of the world’s largest clinical trials to identify important findings beyond symptoms that increase a person’s risk of heart attacks.

About the Opportunity

We are seeking a highly skilled Staff Scientist to lead the design, development, validation of innovative clinical workflow that can directly impact the diagnosis and treatment for heart disease. In this senior-level role, you are responsible for architecting a cutting-edge product that integrates our existing technologies while pushing the boundary of innovation in cardiac vascular imaging. You will also represent the company in strategic research collaborations with leading academic and clinical institutions, driving innovation at the intersection of AI and cardiovascular health.

Key Responsibilities

• Research and develop state-of-the-art AI and non-AI algorithms for coronary CT/fluoroscopy imaging applications.
• Implement efficient and robust image processing pipeline to solve challenging problems in low latency environments.
• Translate product and clinical requirements into algorithmic specifications in collaboration with Product and Clinical teams.
• Partner with Regulatory Affairs to support regulatory submissions (e.g., 510(k), De Novo, PCCP), including generating evidence and documentation.
• Collaborate with engineering teams to deploy AI and non-AI based solutions in clinical practice.
• Communicate findings and strategy to internal stakeholders and leadership through clear technical documentation, presentations, and demos.
• Contribute to intellectual property development through patents and scientific publications.
• Mentor junior scientists and foster a culture of technical excellence and scientific rigor.

Required Qualifications & Skills

• PHD. in Computer Science, Data Science, Biomedical Engineering, Biomedical Imaging, or a related technical field, with 5+ years combined postdoc and/or industry experience; OR an M.S. with 8+ years of relevant experience.
• Applied AI/DL research for medical imaging diagnostics and analysis, classical image processing algorithm, optical flow analysis, 2D&3D rigid/deformable image registration
• Proven track record of successful product delivery in medical imaging domain
• Strong experience in C++ and Python.
• Experience of developing and applying graph processing or GNN(graph neural network)
• Prior experience with ITK, OpenCV, VTK, CMake, Slicer is a plus
• Prior experience with cardiac motion modelling or tracking is a plus
• Excellent interpersonal, cross-functional, and cross-cultural collaboration skills.

Preferred Qualifications

• 5+ years of industry experience in AI-based medical device development or clinical deployment.
• Experience supporting FDA regulatory submissions for ML-based software, including familiarity with De Novo, 510(k), and PCCP pathways.
• Deep domain knowledge in cardiovascular imaging and CT interpretation workflows.

OUR COMPANY IS AN EQUAL OPPORTUNITY EMPLOYER.  We do not discriminate on the basis of race, color, national origin, ancestry, citizenship status, protected veteran status, religion, physical or mental disability, marital status, sex, sexual orientation, gender identity or expression, age, or any other basis protected by law, ordinance, or regulation.

Job duties, activities, and responsibilities are subject to change by our company.

The base salary range for this role varies by location and is aligned to market benchmarks.

• Candidates located in higher-cost labor markets, including California, Washington, New York, New Jersey, Connecticut, Massachusetts, and Washington, DC represent the middle to high end of the range, while candidates located in all other U.S. locations represent the low to middle end of the range.
• Final compensation is determined based on location, experience, skills, and internal equity.

This role is eligible for a 15% target annual bonus, resulting in the following base salary and Total Target Compensation (TTC) ranges:

• Base Salary: $234,000 - $271,000 
• TTC: $268,000 - $311,000

*Total Target Compensation (TTC): Total Cash Compensation (including base pay, variable pay, commission, bonuses, etc.) Additionally, stock options, paid benefits, and employee perks are part of your total rewards.

We are looking for a Lead Staff Data Scientist to join the Marketplace Quality Engineering (MQE) team. MQE is a cross-functional team responsible for the integrity, performance, and trustworthiness of The Trade Desk’s inventory marketplace. We build systems that detect and prevent fraud, measure and improve inventory quality, and optimize marketplace dynamics to deliver better outcomes for advertisers, publishers, and consumers. 

In this role, you will provide technical and strategic leadership within MQE by defining data science roadmap and execution plans, owning end-to-end development of advanced modeling, analytical, and measurement systems, and partnering closely with engineering, product, and business leaders to translate complex requirements into trusted, scalable solutions. 

WHAT YOU’LL DO 

Technical Ownership 

• Own the data science vision and roadmap for MQE initiatives, aligning technical direction with strategic goals and industry trends. 

• Design, build, and productionize statistical and machine learning models to detect fraud, invalid traffic, and low-quality inventory in adversarial, large-scale environments. 

• Define and maintain metrics, experimentation procedures, and monitoring systems to ensure long-term performance. 

• Develop analytical and explainability frameworks that provide clear visibility into how quality initiatives impact inventory supply, advertiser spend, and marketplace dynamics. 

Cross-Functional Impact 

• Collaborate with product and business stakeholders to translate analytical insights into clear, defensible decisions and marketplace enforcement strategies. 

• Partner closely with engineering to deploy scalable, performant models. 

• Anticipate emerging marketplace risks and proactively develop data-driven solutions to protect marketplace integrity. 

Leadership & Mentorship 

• Act as a staff-level technical leader, setting standards for analytical rigor, model evaluation, and scientific best practices across MQE. 

• Mentor and develop data scientists through design reviews, technical guidance, and career coaching. 

• Influence technical direction across teams by driving alignment, knowledge sharing, and a culture of high-quality decision-making. 

WHO WE ARE LOOKING FOR 

• Advanced degree (MS or PhD) in a quantitative field such as Statistics, Computer Science, Economics, Applied Math, Operations Research, or similar. 

• 7+ years of experience working in a DS role that involves bringing products from ideation to production. 

• Deep expertise in statistical modeling, machine learning, and large-scale data analysis. 

• Strong understanding of experimentation, causal inference, and metric design in complex systems. 

• Familiarity with large-scale data and ML tooling (e.g. Spark, distributed training, real-time inference systems). 

• Proven ability to lead ambiguous, high-impact projects end-to-end as a senior individual contributor. 

• Excellent communication skills and the ability to influence across organizational boundaries. 

• Experience in programmatic advertising and/or real-time auctions is a plus. 

• Track record of mentoring senior data scientists and shaping team-level technical direction is a plus. 

About the Opportunity

We are seeking a highly skilled Machine Learning Scientist to drive the development and translation of cutting-edge ML models that have a direct impact on the care pathway for heart disease diagnosis and prognosis. In this role, you will collaborate with ML scientists, data engineers, biostatisticians, regulatory experts, and senior leadership to understand clinical requirements, develop innovative solutions, and support product development and regulatory approvals. You will also engage in high-impact research collaborations with world-renowned academic and medical institutions.

Responsibilities

• Research and develop state-of-the-art machine learning models for coronary CT angiography imaging applications.
• Conduct rigorous analysis and validation of machine learning algorithms and prototypes.
• Explore novel methods for processing and analyzing large, complex medical imaging datasets.
• Collaborate with engineering teams to deploy ML algorithms in clinical practice.
• Present research findings, insights, and recommendations to internal stakeholders and external collaborators.
• Author scientific publications and contribute to patent development.
• Manage collaborative research projects with leading academic partners.

Requirements

• Ph.D. in Computer Science, Data Science, Biomedical Engineering, Biomedical Imaging, or a related technical field; OR an M.S. with 5+ years of relevant experience.
• Strong theoretical and practical expertise in image science, applied mathematics, machine learning, and deep learning.
• Research experience in applying ML and deep learning techniques to medical image processing, including segmentation, registration, classification, reconstruction, and detection.
• Proven track record of publications in top-tier medical imaging or computer vision conferences and journals (e.g., MICCAI, IEEE TMI, CVPR, Medical Image Analysis).
• Proficiency in Python, with experience handling large datasets, implementing ML pipelines, and visualizing analysis results.
• Ability to translate complex clinical requirements into machine learning solutions.
• Strong critical thinking, problem-solving, and project management skills.
• Excellent interpersonal, cross-functional, and cross-cultural collaboration skills.

Preferred Qualifications: 

• 2+ years of postdoctoral research or industry experience.
• Hands-on experience in developing and applying advanced deep learning models, including vision transformers, semi-supervised/self-supervised/unsupervised learning, incremental learning, and continuous learning techniques.
• Strong domain knowledge in CT imaging and its clinical applications.

The base salary range for this role varies by location and is aligned to market benchmarks.

• Candidates located in higher-cost labor markets, including California, Washington, New York, New Jersey, Connecticut, Massachusetts, and Washington, DC represent the middle to high end of the range, while candidates located in all other U.S. locations represent the low to middle end of the range.
• Final compensation is determined based on location, experience, skills, and internal equity.

This role is eligible for a 15% target annual bonus, resulting in the following base salary and Total Target Compensation (TTC) ranges:

• Base Salary: $186,000 - $212,000
• TTC: $214,000 - $245,000

*Total Target Compensation (TTC): Total Cash Compensation (including base pay, variable pay, commission, bonuses, etc.) Additionally, stock options, paid benefits, and employee perks are part of your total rewards.

ABOUT THIS OPPORTUNITY

We are looking for a Data Scientist who views machine learning as a product, not just a research project. You will be a foundational member of our AI team, responsible for designing, building, and deploying sophisticated models that solve complex business problems. You aren't just an expert in XGBoost or Transformers; you are an expert in building the pipelines that make these models reliable, scalable, and impactful.

WHAT YOU'LL DO
^{Essential Job Duties & Functions}

• End-to-End Model Development: Design and implement the full ML lifecycle—from exploratory data analysis (EDA) and feature engineering to model selection, tuning, and validation.
• GCP Architecture: Leverage the full Google Cloud AI suite (Vertex AI, BigQuery ML, Dataflow, and Pub/Sub) to build robust, cloud-native ML solutions.
• MLOps & Engineering: Implement CI/CD for machine learning (CT - Continuous Training) to ensure models remain performant in production environments.
• Strategic Leadership: Partner with stakeholders to translate ambiguous business challenges into technical roadmaps. Mentor junior scientists and advocate for best practices in code quality and experiment tracking.
• Look for opportunities to embed AI as a repeatable co-pilot in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.

WHAT YOU’LL BRING

• 5+ years in a professional Data Science role with a track record of deploying models at scale.
• Proficiency in Vertex AI, BigQuery, Cloud Storage, and Looker. Experience with Kubeflow is a major plus.
• Expert-level Python (pandas, scikit-learn, PyTorch/TensorFlow), Spark, and advanced SQL.
• Deep understanding of statistics and ML theory (e.g., Gradient Descent, Bias-Variance tradeoff, Bayesian inference).
• Experience with ETL/ELT processes, specifically using dbt.
• A strong curiosity for exploring new technologies, including AI
• A shared passion for and ability to demonstrate onX’s Company Values.
• Permanent US work authorization is a condition of employment with onX.

Our Tech Stack

• Data Warehouse: BigQuery
• Orchestration: Airflow (Cloud Composer)
• Modeling: Vertex AI Pipelines, JupyterLab
• Deployment: Docker, GKE (Google Kubernetes Engine)

Pro Tip for the Candidate: We value "clean code" as much as "smart math." If you treat your notebooks like production scripts and your Git history is a work of art, you’ll fit right in.

What Sets You Apart

• The "Product" Mindset: You understand that a model with 99% accuracy is useless if it costs more to run than the value it creates.
• Infrastructure as Code: You are comfortable with Terraform or similar tools to manage your cloud resources.
• Communication: You can explain the "why" behind a complex neural network architecture to an executive without using jargon.

THE ONX EXPERIENCE

onX is a distributed company with more than 400 employees across the country. We come together regularly to work in person and stay connected through regional basecamps and a culture that balances individual ownership with deep collaboration.

While we move quickly, we’re not a scrappy start-up. We operate with clear goals, structure, and frameworks that guide how we prioritize and execute. Priorities matter. While they may shift, data shapes how we evolve as our business, products, and the world around us change.

Clear priorities and structure don’t limit ownership - they make it possible. You’ll have the autonomy to define your work and make meaningful decisions within clear strategic boundaries. You’ll partner closely with others to solve complex problems and build solutions that scale across teams and platforms. Along the way, you’ll be supported with feedback, tools, and opportunities to grow your craft as you take on new challenges.

WHERE YOU CAN WORK

onX has created a thriving distributed workforce designed to foster connection, collaboration, and shared experience across several US locations. We have two HQ locations in Bozeman and Missoula, MT and established virtual workforce Basecamps in Austin, TX; Denver, CO; Kalispell, MT; Minneapolis, MN; Portland, OR; Salt Lake City, UT; and Seattle, WA.

HOW YOU’LL BE COMPENSATED

onX is committed to compensating all employees fairly and equitably for their contributions. For this position, applicants can expect to make between $126,000 to $149,000 upon hire. The pay range will vary based on experience, skills, certifications, and education among other factors as required in the job description. In addition, full-time onX employees are eligible for a grant of common share options with a vesting schedule and a potential annual bonus of 10% based on company performance.

WHAT WE’RE OFFERING YOU

• Competitive salaries, annual bonuses, equity, and opportunities for growth
• Comprehensive health benefits, including a no-monthly-cost medical plan
• Paid parental leave of 13 weeks for birthing parents and 5 weeks for non-birthing parents
• 401k matching at 100% for the first 3% you save and 50% from 3-5%
• Company-wide outdoor adventures and amazing outdoor industry perks
• Annual “Get Out, Get Active” funds to fuel your active lifestyle
• Flexible time away package that includes PTO, STO, VTO, and paid holidays

PERFORMANCE ESSENTIALS

In this role, success is driven by cognitive abilities such as concentration and problem-solving, essential for our computer-centric tasks. onX will explore reasonable accommodations to ensure that individuals with diverse abilities can fully engage in and contribute to the essential physical and mental functions of the job. If you need assistance or accommodation, please contact us at PC@onxmaps.com. 

Application Deadline is [day of week], [month] [day] at [0:00 pm] MST

Position open until filled. 

#LI-Remote

Role Summary

Spring Fertility provides exceptional patient care and our Lab Technicians are essential to establishing an excellent experience for all our patients. 

Some day-to-day responsibilities include: 

• Conduct semen analysis, including strict morphology and sperm antibody screening 
• Prepare semen for intrauterine insemination and in vitro fertilization procedure 
• Sterilization of lab and equipment 
• Cryopreservation, thawing of sperm and testicular tissue 

Our ideal candidate has a Bachelor’s degree in biological sciences, is familiar with the lab environment and comfortable engaging professionally with patients. 

Education, Licenses, Certifications

• Bachelor of Science degree 
• Clinical Laboratory Technician (CLT) or Medical Laboratory Scientist (MLS) certification required

Employment Type

This is a full-time non-exempt onsite position that requires early hours, rotational weekends and holidays. 

Compensation

The salary range for this role is $55,000 - $65,000. Salary is based on several factors including job related knowledge and skill set, depth of experience, certifications and/or degrees. 

#INDSFT

Xometry is seeking a Principal Data & ML Scientist to join our Generative AI team. The ideal candidate will have a passion for advancing machine learning and generative AI capabilities, particularly for fine-tuning generative and language models, multimodal document understanding, and structured data extraction. This person will leverage their expertise in generative models and data science to develop and optimize innovative AI-driven solutions that enhance Xometry's service offerings.

Responsibilities: 

• Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring the team follows industry standards in AI and ML development.
• Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them with Xometry’s business objectives.
• Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents.
• Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models.
• Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models.
• Utilize cloud platforms (e.g., Amazon Web Services) for large-scale data processing, model training, and deployment.
• Collaborate with cross-functional teams, including engineering and business teams, to align generative AI solutions with business needs and drive impactful applications.
• Mentor and guide team members on advanced machine learning techniques, model architecture design, and problem-solving strategies to elevate the team’s technical capabilities.
• Continuously experiment and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency in a fast-paced, agile environment.
• Stay updated with the latest research in generative AI, deep learning, and multimodal data processing, incorporating best practices and advancements into model development.

Qualifications:

• A bachelor’s degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
• 7+ years of experience in data science and machine learning, focusing on generative models, LLMs, or computer vision.
• Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs).
• Experience with multimodal data processing (e.g., combining text, image, and 3D data).
• Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy.
• Strong background in probability, statistics, and optimization techniques relevant to generative modeling.
• Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker).
• Familiar with software engineering principles, including version control, reproducibility, and continuous integration.
• Experience in the manufacturing, supply chain, or similar industries is a plus.

The estimated base salary range for new hires into this role is $164,000- $213,000 annually + annual bonus depending on factors such as job-related skills, relevant experience, and location. We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.

#LI-Hybrid

Pinnacol goes beyond providing Workers’ Compensation insurance to Colorado businesses. We are a technology first company that believes in making a meaningful impact in workers’ lives across Colorado in their most difficult moments  by designing solutions that effectively help them get the care they need. We enable our policyholders to report a claim with a mobile first experience, all while providing insurance quotes to agents and new clients in 5 minutes or less through our award-winning app. 

These customer-focused experiences are built on nimble platforms capable of using the latest and greatest technology available. Our Tech Stack includes:

Salesforce 

React 

Python

Gitlab

Google Cloud Platform

• Cloud Functions, AppEngine and AppScript
• Pub/Sub
• BigQuery
• Cloud Composer (Apache Airflow)
• Cloud SQL (PostgreSQL)
• Storage
• Secrets Manager
• Kubernetes (GKE)

Hashicorp Terraform and Vault

This is about more than shiny code and sleek design. Pinnacol’s culture sets us apart. We listen to our customers to create experiences with their insights in mind. We actively seek feedback from our injured workers and policyholders through surveys, focus groups, feature testing and research. It feels like family at Pinnacol. We do virtual team building and happy hours using Zoom and JackboxTV Games. We grow talent from within. There are opportunities for continued development and support for learning new skills, even those outside your current role. Our teams and leaders value collaboration and experimentation so we constantly learn how to do things better..

As one of the largest teams at Pinnacol, Information Services invests in a variety of opportunities for those who love tech. Pinnacol’s charge is to “Lead a revolution in caring” and  our commitment to innovation and building cool stuff requires amazing talent. Here are a few of the roles we’ve recently hired:

• Salesforce Engineer
• Data Engineer
• Data Scientist
• Machine Learning Engineer
• Natural Language Processing Engineer
• Database Engineer
• Cloud Architect
• ECM Administrator
• QA Engineer

Pinnacol has over 100 years of knowing and understanding Colorado workers and businesses. With a century of experience behind us, we’re out to tackle the big problems that these individuals and communities face. By always asking “What’s next?”, our agile and creative solutions keep us on the leading edge of creating better ways to care for and protect the people and businesses we serve.