Careers at ORM Technologies

ORM Technologies is a leading Predictive Revenue Analytics company delivering innovative SaaS solutions to B2B sales and marketing teams. Our platform helps customers analyze performance, forecast revenue, and optimize decision-making to maximize growth.

We are looking for a highly motivated Data Science Intern to work in a dynamic startup environment and contribute to machine learning and statistical forecasting models. This role offers a hands-on opportunity to develop predictive models, analyze large datasets, and gain real-world experience in applying AI/ML to revenue analytics. If you’re passionate about data-driven decision-making and building impactful machine-learning solutions, ORM Technologies is the place for you!

Role and Responsibilities

• Develop and enhance machine learning models for predictive analytics.
• Build and refine statistical forecasting models to improve revenue predictions.
• Perform data preprocessing, transformation, and feature engineering on large datasets.
• Evaluate and compare models using statistical performance metrics (e.g. ROC-AUC).
• Collaborate with software engineers to integrate ML models into production systems.
• Create visualizations to communicate insights to both non-technical stakeholders.
• Research emerging AI/ML techniques and explore innovative solutions for sales and marketing analytics.

Expect to Learn

• End-to-end machine learning workflows, from data collection to model deployment.
• Advanced techniques in statistical forecasting, time series modeling, and predictive analytics.
• Best practices in feature selection, model validation, and hyperparameter tuning.
• How to work R for data science applications.
• How to collaborate with software engineers and business stakeholders to implement AI-driven solutions.

Skills and Requirements

• Pursuing a degree in Operations Research, Data Science, Statistics, Mathematics.
• Strong foundation in machine learning, statistical modeling, and data analytics.
• Proficiency in R or Python for data manipulation, modeling, and visualization.
• Ability to translate business requirements into actionable ML models.
• Strong problem-solving skills and ability to communicate technical concepts clearly.

Other Desirable Skills

• Exposure to data visualization tools in BI platforms (e.g., Power BI, Tableau).
• Interest in optimization techniques and operations research for revenue analytics.
• Familiarity with cloud computing platforms (AWS, Azure) and version control tools (Git).
• Understanding of data engineering concepts, including handling large-scale datasets.

ORM Technologies is a leading Predictive Revenue Analytics company delivering innovative AI-powered SaaS solutions to B2B sales and marketing teams. Our platform helps customers analyze performance, forecast revenue, and optimize decision-making to maximize growth.

We are looking for a highly motivated Software Developer Intern eager to work in a startup environment and contribute to real-world analytics applications. This role offers a hands-on opportunity to work on full-stack development, data-driven insights, and software optimization alongside experienced engineers. If you’re passionate about building scalable software and working with cutting-edge analytics, ORM Technologies is the place for you!

Role and Responsibilities

• Full-stack software development, including both front-end and back-end tasks.
• Design and implementation of new and existing features in our SaaS platform.
• Data extraction, transformation, and import to support analytics and reporting.
• Client data analysis and reporting, delivering insights to improve performance.

Expect to Learn

• Full-Stack Development in a Fast-Paced SaaS Startup.
• Advanced Ruby on Rails development, including best practices and framework intricacies.
• Writing and executing automated tests using RSpec for high-quality software.
• Optimizing SQL queries and database interactions through Rails’ ActiveRecord.
• Data manipulation techniques to handle large and diverse datasets efficiently.
• Working within an agile development team using Git and version control workflows.

Skills and Requirements

• Pursuing a degree in Computer Science, Computer Engineering, or a related field.
• Strong foundation in object-oriented programming (OOP) and software design principles.
• Basic understanding of SQL, relational databases, and schema design.
• Comfortable working in a Linux environment and using Git for version control.
• Familiarity with JavaScript, HTML, and CSS for front-end development.
• Excellent problem-solving skills and the ability to clearly communicate technical concepts.

Other Desirable Skills

• Experience with Ruby on Rails.
• Familiarity with data science concepts, analytics, or business intelligence (BI).
• Exposure to Python, R, or mathematical modeling (GAMS, Gurobi, linear programming, etc.).
• Understanding of AI/ML-driven analytics or statistical modeling.
• Ability to think critically, analyze large datasets, and optimize performance.

ORM Technologies is a predictive revenue analytics company delivering SaaS solutions to B2B sales and marketing teams. Our platform helps customers analyze performance, forecast revenue, and optimize decisions that drive measurable growth. ORM is advancing its AI platform by combining machine learning, statistical forecasting, optimization, and large language models to deliver explainable, actionable, and conversational analytics.

We are seeking a Data Scientist – Applied AI & Machine Learning to play a central role in shaping both the analytical capabilities of the ORM platform and the insights delivered directly to customers. This role owns predictive modeling and forecasting while contributing to AI features that integrate LLMs with structured ML and optimization models. Approximately 30% of this role is customer-facing, focused on translating analytics into trusted, decision-ready insights.

This position is ideal for someone who wants to build production-grade predictive systems, influence product direction, and engage directly with customers while partnering with GTM business leaders.

Role and Responsibilities

• Own the development, validation, and improvement of machine learning and statistical models used for revenue prediction, propensity modeling, and performance analytics.
• Design, build, and maintain time series and forecasting models embedded in customer-facing workflows.
• Contribute to AI features that combine large language models with predictive, forecasting, and optimization outputs to deliver explainable and conversational insights within the ORM platform.
• Spend approximately 30% of time working directly with customers to understand objectives, translate business questions into analytical approaches, and present findings and recommendations.
• Participate in customer meetings, model reviews, and working sessions to explain model assumptions, behavior, results, and tradeoffs.
• Partner with software engineers to productionize models and ensure scalability, reliability, and performance.
• Develop feature engineering pipelines and modeling frameworks that support continuous learning and improvement.
• Evaluate models using statistical, machine learning, and business performance metrics and communicate results clearly.
• Stay current on emerging ML, AI, and LLM techniques and assess their applicability to ORM’s platform and customer use cases.

What You will Build and Learn

• Production-grade machine learning and forecasting systems embedded in a SaaS platform.
• Applied AI solutions that combine deterministic models, probabilistic ML, optimization, and LLM-driven interfaces.
• Advanced forecasting and time series techniques applied to real-world revenue and go-to-market data.
• Best practices for model validation, monitoring, and lifecycle management.
• The ability to influence both product direction and customer strategy through data-driven insight.

Skills & Requirements

• Master’s degree in Statistics, Mathematics, Operations Research, or a related quantitative field.
• 1–3 years of professional experience applying machine learning, statistical modeling, or advanced analytics in a production or customer-facing environment.
• Strong foundation in machine learning, statistical modeling, and data analysis.
• Proficiency in R or Python for data manipulation, modeling, and visualization.
• Experience working with real-world, messy datasets and ambiguous problem definitions.
• Interest in applied AI, including the integration of large language models with structured data, predictive models, and optimization outputs.
• Strong communication skills and comfort engaging directly with customers and business stakeholders.

Other Desirable Skills

• Experience supporting analytics or data science work in customer-facing, consulting, or SaaS environments.
• Familiarity with cloud platforms such as AWS or Azure and version control tools like Git.
• Interest in mathematical optimization methods and operations research applied to revenue and go-to-market analytics.
• Understanding of data engineering fundamentals, including pipelines and large-scale data processing.
• Understanding of MLOps.

Benefits

• 401(k) with matching
• Medical
• Dental

ORM Technologies is a predictive revenue analytics company delivering SaaS solutions to B2B sales and marketing teams. Our platform helps customers analyze performance, forecast revenue, and optimize decisions that drive measurable growth. ORM is advancing its AI platform by combining machine learning, statistical forecasting, optimization, and large language models to deliver explainable, actionable, and conversational analytics.

We are seeking a Data Scientist – Applied AI & Machine Learning to play a central role in shaping both the analytical capabilities of the ORM platform and the insights delivered directly to customers. This role owns predictive modeling and forecasting while contributing to AI features that integrate LLMs with structured ML and optimization models. Approximately 30% of this role is customer-facing, focused on translating analytics into trusted, decision-ready insights.

This position is ideal for someone who wants to build production-grade predictive systems, influence product direction, and engage directly with customers while partnering with GTM business leaders.

Role and Responsibilities

• Own the development, validation, and improvement of machine learning and statistical models used for revenue prediction, propensity modeling, and performance analytics.
• Design, build, and maintain time series and forecasting models embedded in customer-facing workflows.
• Contribute to AI features that combine large language models with predictive, forecasting, and optimization outputs to deliver explainable and conversational insights within the ORM platform.
• Spend approximately 30% of time working directly with customers to understand objectives, translate business questions into analytical approaches, and present findings and recommendations.
• Participate in customer meetings, model reviews, and working sessions to explain model assumptions, behavior, results, and tradeoffs.
• Partner with software engineers to productionize models and ensure scalability, reliability, and performance.
• Develop feature engineering pipelines and modeling frameworks that support continuous learning and improvement.
• Evaluate models using statistical, machine learning, and business performance metrics and communicate results clearly.
• Stay current on emerging ML, AI, and LLM techniques and assess their applicability to ORM’s platform and customer use cases.

What You will Build and Learn

• Production-grade machine learning and forecasting systems embedded in a SaaS platform.
• Applied AI solutions that combine deterministic models, probabilistic ML, optimization, and LLM-driven interfaces.
• Advanced forecasting and time series techniques applied to real-world revenue and go-to-market data.
• Best practices for model validation, monitoring, and lifecycle management.
• The ability to influence both product direction and customer strategy through data-driven insight.

Skills & Requirements

• Master’s degree in Statistics, Mathematics, Operations Research, or a related quantitative field.
• 1–3 years of professional experience applying machine learning, statistical modeling, or advanced analytics in a production or customer-facing environment.
• Strong foundation in machine learning, statistical modeling, and data analysis.
• Proficiency in R or Python for data manipulation, modeling, and visualization.
• Experience working with real-world, messy datasets and ambiguous problem definitions.
• Interest in applied AI, including the integration of large language models with structured data, predictive models, and optimization outputs.
• Strong communication skills and comfort engaging directly with customers and business stakeholders.

Other Desirable Skills

• Experience supporting analytics or data science work in customer-facing, consulting, or SaaS environments.
• Familiarity with cloud platforms such as AWS or Azure and version control tools like Git.
• Interest in mathematical optimization methods and operations research applied to revenue and go-to-market analytics.
• Understanding of data engineering fundamentals, including pipelines and large-scale data processing.
• Understanding of MLOps.

Benefits

• 401(k) with matching
• Medical
• Dental