Who We Are: HelioCampus was founded with the purpose of helping college & university leaders navigate today’s growing pressures. As one of EdTech’s most steadily growing companies, our roots in higher ed ground us in the critical nature of this work.
What We Do:We help our clients navigate today’s high stakes with data and Institutional Performance Management practices. Together with our clients, we chart a path to sustainability by borrowing practices from the most successful businesses.
How We Do It:
We approach our work with a “we’re on it” attitude that the higher ed community has come to know and expect from our team. We’re data geeks to our core, committed to simplifying the toughest challenges and operating with transparency. Our most successful team members are change agents who love a challenge.
How You'll Help:Bringing experience analyzing student-level data at a Higher Ed institution or EdTech company in the areas of admissions, enrollment, financial aid, student success, institutional effectiveness, or finance and budget, you will step into a key role within HelioCampus’ Client Experience division. As a member of the DS-OPS (Data Science Operations, Products, and Services) team, you will partner directly with university leadership to turn "business questions" into "data questions," delivering analyses and predictive models that support institutional decision-making.
In this role, you will work independently and collaboratively with engineers and clients to design datasets, perform statistical analysis, build dashboards, and deploy machine learning models. Managing your projects autonomously, you will use your strong communication skills to translate complex analytical results into clear, actionable insights for a variety of higher education stakeholders.
What You Will Do:
Communicate with stakeholders to determine institutional goals, and design analyses and data visualizations to provide insight to complex business problems.
Conduct exploratory data analysis in collaboration with subject matter experts to build and validate analytical datasets.
Develop statistical and machine learning models (classification, time series, etc.) using a custom python framework to generate scores and forecasts.
Present predictive modeling results and operational dashboards to end-users at colleges and universities to help them understand and make use of the findings and scores.
Work with data science and data engineering teams to build data pipelines, improve internal systems, and deploy and maintain models in a production environment.
Collaborate with other data scientists to share knowledge, develop best practices, and contribute to documentation, process standardization, and product development.
Occasionally travel (typically 1-3 days at a time, ~3 times per year) to HelioCampus offices and client sites for meetings and presentations.
You Will Be a Good Fit For This Role If You Have:
Experience analyzing student-level data at a Higher Ed institution or EdTech company in the areas of admissions, enrollment, financial aid, student success, institutional effectiveness, or finance/budget.
3+ years of experience delivering analytical insights to higher ed stakeholders, including building and evaluating machine learning models (python and scikit-learn experience required).
Analytical dataset design and feature engineering skills (SQL experience required).
Ability to conduct, interpret, and explain statistical analyses.
Experience using interactive data visualization and business intelligence tools (Tableau and/or Power BI) to design and publish interactive reports and dashboards, enabling data exploration and communication of analysis results.
Excellent communication and collaboration skills, and experience working with both business users and technical development teams, as well as presenting findings to decision-makers.
Experience working with student data from PeopleSoft, Banner, Colleague, Workday, Slate, Salesforce/TargetX, or other higher ed-specific data systems
Ability to work effectively and independently in a remote role on an Eastern time zone business hour schedule , managing multiple priorities and meeting deliverable deadlines.
Understanding of model transparency & explainability concepts, and ethical issues in data science.
Familiarity with production data pipeline and model deployment and management.
Familiarity with relational database and data warehouse concepts.
Familiarity with a variety of machine learning methodologies, forecasting techniques, and generative AI (LLMs).
A tool-agnostic approach to data science: excitement for adopting new tools and techniques, while having solid fundamentals that underpin quick learning and high quality work delivery.
Nice To Have’s Include:
Advanced degree in an analytical/quantitative field (Comparable depth of experience can be substituted for quantitative field of study or advanced degree).
Experience working remotely with distributed teams and clients.
Experience with version control (git), software development processes, object oriented programming, and machine learning framework development.
MLOps experience deploying and maintaining production pipelines and models.
Experience applying a wide range of supervised and unsupervised machine learning and forecasting techniques using a variety of python packages.
Experience working with any of the following tools: jupyter notebooks, pandas, Docker, linux server/command line, EC2, S3, Amazon Redshift, airflow, SHAP, MLFlow, prophet, VS Code.
Experience using AI tools/services to increase delivery efficiency without sacrificing quality (for example - having built enough depth of coding experience to critically evaluate AI-generated code and avoid introducing issues that lead to future rework).
Experience with LLM Evaluation methods and frameworks.
Example Projects You May Work On:
Developing classification models to predict admitted student yield, enrolled student retention, or on-time graduation, and presenting results to university leaders designing programs to improve student outcomes and support institutional success.
Designing and publishing interactive dashboards to enable end-users to operationalize model results to make an impact at colleges and universities.
Helping institutional stakeholders understand financial need and aid correlation with student success metrics.
Forecasting enrollments using time-series methods to support budgeting and hiring decisions.
Partnering with senior Data Scientists and other colleagues to improve our products and processes using new techniques, tools, and AI.
Contributing to extensible python machine learning development and deployment framework.
Documenting data pipelines, ML workflows, and deployed models for both internal teams and client end-users.
Presenting webinars about our team’s work to current and prospective clients.
A Note on AI in Our Hiring Process:
We are an AI-forward company and champion the smart use of technology. However, our hiring process is designed to evaluate your personal capabilities, critical thinking, and lived experience. Please ensure your resume, application materials, and interview responses are your own and not generated by AI. Show us your raw talent and your genuine experience, that is the person we want to join our team.
Location:
This specific role is primarily remote, with occasional travel to an office or client site. US East Coast working hours are required, and a strong preference is given to candidates who can easily travel to our Chapel Hill, NC or Bethesda, MD offices for occasional in-person work.
Compensation and Benefits:
Flexible work schedule, 18 PTO days on day one with additional PTO per year. Fifteen (15) paid holidays, medical/dental/vision coverage, parental leave, 401K with match, company events, referral bonus, professional development opportunities, home office perks, and two office locations.
What Sets Us Apart:
1. Commitment to Higher Education:We believe that serving higher ed makes the world a better place. This drives our desire to deliver high-quality products and services to help higher education institutions serve their students and communities.
2. Flexibility to Fit Your Life:HelioCampus employees enjoy the autonomy, freedom, and trust of a remote-first working environment. We embrace an “on it” mentality both in and out of the workplace, and employees are supported in pursuing personal and professional passions.
3. A Community of Bright Minds with Big Hearts:HelioCampus hires curious and talented practitioners who bring a diversity of thought and genuine care for one another and our clients to work every day. Our team members are more than a job description and are encouraged to show up as their full and authentic selves.
What We Believe:
HelioCampus is an equal opportunity employer, and all qualified candidates will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.
Disclaimer:
The list of responsibilities described above is not comprehensive. Other tasks not mentioned here may be required. Changing business conditions may trigger changes to job responsibilities. This job description is not an employment contract.
Physical Qualifications:
This position requires the following physical qualifications to support a productive remote work environment. We are dedicated to providing reasonable accommodations for individuals with disabilities to perform the essential functions of this role. If you require accommodations, please discuss this during the application process.
Vision:Sufficient visual acuity to read documents, view computer screens, and engage in tasks that require attention to detail.
Hearing:Ability to communicate effectively in person (as applicable) and via phone or video conferencing, ensuring clear understanding of verbal instructions.
Fine Motor Skills:Proficient use of hands for typing, using a mouse, and managing office equipment such as printers and scanners.
Lifting:Occasional lifting of up to 10 pounds (e.g., office supplies or equipment).
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