About Equip

Equip is the leading virtual, evidence-based eating disorder treatment program on a mission to ensure that everyone with an eating disorder can access treatment that works. Created by clinical experts in the field and people with lived experience, Equip builds upon evidence-based treatments to empower individuals to reach lasting recovery. All Equip patients receive a dedicated care team, including a therapist, dietitian, physician, and peer and family mentor. The company operates in all 50 states and is partnered with most major health insurance plans. Learn more about our strong outcomes and treatment approach at www.equip.health.

Founded in 2019, Equip has been a fully virtual company since its inception and is proud of the highly-engaged, passionate, and diverse Equisters that have created Equip’s culture. Recognized by Time as one of the most influential companies of 2023, along with awards from Linkedin and Lattice, we are grateful to Equipsters for building a sustainable treatment program that has served thousands of patients and families.

About the Role

This Data Scientist II will be responsible for building and operationalizing statistical models, ML/AI solutions, and interactive dashboards to support strategic workforce planning and operational decision-making in the telehealth space. This role focuses on using data science to optimize workforce resource allocation, capacity planning, and forecasting across a variety of business domains at Equip. You will help develop and implement data-driven solutions to problems such as optimizing clinical staffing, predicting employee attrition, and proactively identifying shortages and gaps in various resources. The data scientist will partner with the Operations, People, and Finance teams to translate business needs into actionable insights and analytic solutions.

As part of the Data and Insights team, the Data Scientist II will collaborate with a diverse group of data scientists, analysts, engineers, and product managers to work on exciting projects and contribute to the growth of Equip.

Responsibilities

• Develop and deploy analytic models for workforce demand forecasting, resource optimization, and capacity planning.

• Implement workforce allocation algorithms to optimize staffing and resource allocation.

• Design and develop models/algorithms based on predictive/descriptive statistical modeling, machine learning, and LLMs/AI to glean insights from large datasets.

• Continuously monitor and implement data quality processes to ensure accuracy, consistency, and reliability.

• Clean, transform, and optimize data for analysis.

• Utilize CI/CD pipelines and APIs to deploy models and algorithms to target environments.

• Work with cross-functional teams to understand needs and identify how data science can support operational, workforce planning, and business goals.

• Perform analyses, visualize data, and present data science work to stakeholders.

• Perform other duties as assigned.

Qualifications

• Bachelors or Masters degree in statistics, data science, or related field.

• 2-4+ years of demonstrated work experience in data science, machine learning, or statistics.

• Strong theoretical and practical understanding of statistical analyses (e.g., hypothesis testing, regression, A/B testing), machine learning techniques (e.g., time series forecasting, supervised/unsupervised learning, etc.) and large language/AI models.

• Proficient in Python (pandas, numpy, scikit-learn, etc.) and SQL for data extraction, modeling, preparation, analysis, and model building.

• Experience in workforce optimization, workforce planning, or HR analytics.

• Experience using data visualization software (e.g., Power BI, Tableau) for report creation and dashboard design.

• Ability to write clear, maintainable, extensible, and testable code.

• Experience with Git / GitHub.

• Independent, organized, and solutions-driven.

• Comfortable in a fast-paced environment that is subject to rapid change and innovation.

Benefits

Time Off:

• Flex PTO policy (3-5 wks/year recommended) + 11 paid company holidays.

Medical Benefits:

• Competitive Medical, Dental, Vision, Life, and AD&D insurance.

• Equip pays for a significant percentage of benefits premiums for individuals and families.

• Maven, a company paid reproductive and family care benefit for all employees.

• Employee Assistance Program (EAP), a company paid resource for mental health, legal services, financial support, and more!

Other Benefits

Work From Home Additional Perks:

• $50/month stipend added directly to an employee’s paycheck to cover home internet expenses.

• One-time work from home stipend of up to $500.

Physical Demands

Work is performed 100% from home with no requirement to travel. This is a stationary position that requires the ability to operate standard office equipment and keyboards as well as to talk or hear by telephone. Sit or stand as needed.

At Equip, Diversity, Equity, Inclusion and Belonging (DEIB) are woven into everything we do. At the heart of Equip’s mission is a relentless dedication to making sure that everyone with an eating disorder has access to care that works regardless of race, gender, sexuality, ability, weight, socio-economic status, and any marginalized identity. We also strive toward our providers and corporate team reflecting that same dedication both in bringing in and retaining talented employees from all backgrounds and identities. We have an Equip DEIB council, Equip For All; also referred to as EFA. EFA at Equip aims to be a space driven by mutual respect, and thoughtful, effective communication strategy - enabling full participation of members who identify as marginalized or under-represented and allies, amplifying diverse voices, creating opportunities for advocacy and contributing to the advancement of diversity, equity, inclusion, and belonging at Equip.

As an equal opportunity employer, we provide equal opportunity in all aspects of employment, including recruiting, hiring, compensation, training and promotion, termination, and any other terms and conditions of employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, familial status, age, disability, weight, and/or any other legally protected classification protected by federal, state, or local law.

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