Manager Machine Learning

Key Skills

Algorithms, Cloud computing, Data Analysis, Deep Learning, Machine learning techniques, Natural Language Processing (NLP), Python Programming, PyTorch, SQL, Statistical modeling, TensorFlow, XGBoost

Job Description

Cambia Health Solutions is working to create a seamless and frictionless health care experience for consumers nationwide. This presents a unique challenge and opportunity for innovative solutions that serve patients and providers and influence the healthcare system. Cambia’s AI team builds, prototypes, and deploys data-driven models and algorithms to production systems, delivering more equitable, effective, and affordable health care to our members.

We are seeking an experienced and visionary Machine Learning Manager to help lead our growing team of machine learning scientists and engineers. The AI team applies machine learning, deep learning, and NLP to deliver better health care to Cambia health plan members. We contribute broadly across the company, working on a wide range of challenging problems, for instance:

• Reducing our members’ claim costs using both supervised and unsupervised approaches.
• Speeding up prior authorizations and appeals using NLP to understand clinical notes.
• Personalizing member engagement to promote the health and well-being of our members.
• Driving health equity across Cambia initiatives.
• And much more!

As a Machine Learning Manager, you will be responsible for driving the development and implementation of machine learning solutions, managing projects and resources, and ensuring the successful delivery of ML initiatives. Your strong technical expertise and leadership skills will be crucial in shaping Cambia’s machine learning strategy and driving innovation. If you are interested in an opportunity to lead a talented team and shape the future of our machine learning initiatives, we would love to hear from you.

Qualifications & Requirements:

• Academic degree (Master's or PhD preferred) in Data Science, Computer Science, Engineering, or a related field.
• Minimum of 3 years of experience leading and managing machine learning projects and teams in cloud-based production settings.
• Machine learning expertise: In-depth knowledge of machine learning/deep learning/NLP algorithms, statistical modeling, and data analysis. Experience with cloud-based development and deployment of ML models using standard frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, XGBoost, etc.
• Leadership and management skills: Strong leadership, coaching, and mentorship abilities. Ability to inspire and motivate team members towards achieving goals and delivering high-quality results.
• Project management skills: Proficient in project management methodologies and tools. Ability to manage multiple projects, allocate resources effectively, and meet deadlines. Strong organizational and problem-solving skills.
• Communication and stakeholder management: Excellent communication and interpersonal skills to collaborate effectively with cross-functional teams and stakeholders. Ability to translate technical concepts into non-technical terms and influence decision-making at various levels.
• Innovation and continuous learning: Passion for innovation and staying at the forefront of machine learning advancements. Proven track record of implementing innovative solutions and driving continuous improvement. Active participation in industry conferences, publications, or open-source contributions is a plus.
• Ethical AI: Understanding of ethical considerations and responsible AI practices in machine learning. Familiarity with fairness, bias mitigation, privacy, and security aspects of machine learning models.
• Healthcare knowledge: Previous experience is beneficial but not required.

Responsibilities:

• Team leadership and management: Lead and mentor a team of machine learning scientists and engineers. Provide technical guidance, coaching, and support to team members. Foster a collaborative and inclusive team culture that encourages innovation, growth, and continuous learning.
• Project management: Oversee the end-to-end lifecycle of machine learning projects. Define project scope, objectives, timelines, and resource allocation. Ensure efficient and technically-sound project execution that meets business requirements, including data collection, preprocessing, modeling, evaluation, and deployment.
• Model development and optimization: Guide the team in designing and developing machine learning models that address complex business problems. Collaborate with team members to optimize models for performance, scalability, and robustness. Promote the use of best practices and effective approaches and techniques.
• Cross-functional collaboration: Collaborate with partners and stakeholders, including business leaders, engineers, and product and project managers, to understand requirements and integrate machine learning solutions into products and services. Foster strong partnerships and effective communication across teams.
• Technical expertise and innovation: Stay updated with the latest advancements in machine learning, deep learning, NLP, and related fields, particularly in healthcare applications. Drive innovation by exploring new algorithms, technologies, and tools that can enhance the AI team’s machine learning capabilities.
• Performance monitoring and evaluation: Establish metrics and frameworks for evaluating and tracking the performance and impact of machine learning models and solutions, in both development and production settings. Report on KPIs and provide actionable insights to stakeholders. Continuously iterate and improve models based on feedback and real-world data.
• Machine learning strategy: Contribute to and execute the organization's machine learning strategy. Identify and weigh in on areas where machine learning can provide the most value and competitive advantage.
• Compliance and ethical considerations: Ensure compliance with relevant regulations and ethical guidelines in the development and deployment of machine learning models. Promote fairness, transparency, and accountability in all aspects of machine learning initiatives.

Work Environment:

• Work primarily performed in a hybrid environment consisting of in-office and working from home. 
• Travel may be required, locally or out of state. 

The base pay annual salary range for this job is $147,500 - $240,000.

Base pay is just part of the compensation package at Cambia that is supplemented with an exceptional 401(k) match, bonus opportunity and other benefits. In keeping with our Cause and vision, we offer comprehensive well-being programs and benefits, which we periodically update to stay current. Some highlights:

• medical, dental, and vision coverage for employees and their eligible family members
• annual employer contribution to a health savings account ($1,200 or $2,500 depending on medical coverage, prorated based on hire date)
• paid time off varying by role and tenure in addition to 10 company holidays
• up to a 6% company match on employee 401k contributions, with a potential discretionary contribution based on company performance (no vesting period)
• up to 12 weeks of paid parental time off (eligible day one of employment if within first 12 months following birth or adoption)
• one-time furniture and equipment allowance for employees working from home
• up to $225 in Amazon gift cards for participating in various well-being activities. for a complete list see our External Total Rewards page.

We are an Equal Opportunity and Affirmative Action employer dedicated to workforce diversity and a drug and tobacco-free workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, age, sex, sexual orientation, gender identity, disability, protected veteran status or any other status protected by law. A background check is required.

If you need accommodation for any part of the application process because of a medical condition or disability, please email CambiaCareers@cambiahealth.com.