Machine Learning Scientist Intern
Cambia Health Solutions

Machine Learning Scientist Internship

Remote in ID, OR, UT or WA

This full-time twelve-week internship position is scheduled to begin in May/June 2023

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 and disruptive solutions from the Cambia DTS Artificial Intelligence (AI) Team.

Looking for a passionate, talented and inventive Machine Learning Scientist intern to help design, develop and build industry-leading data science solutions using machine learning technologies and advanced statistical analyses. Together with a highly multi-disciplinary team of scientists, engineers, strategic partners, and subject domain experts, you will work on building a real product with machine learning at its core. Machine Learning Scientist interns work on the difficult problems people encounter when they interact with the healthcare system. We have complex data and challenging real world healthcare problems where machine learning may offer the only solution. This is a team of machine learning scientists, data scientists, and engineers that are passionate about healthcare, and work closely to grow and develop each other.

As a machine learning scientist intern, you will own your work from proof of concept to production and see the real-world impact it has; have autonomy to find creative solutions to difficult and ambiguous business and technical problems; and work with the business and product owners to identify new opportunities to apply ML to impact the healthcare consumer. Improving healthcare is a hard work, but you will never be bored. This is a 12-week summer internship (timeline can be flexible) where you will be directly contributing to the development and deployment of machine learning systems to solve real world problems in healthcare.

Essential Function of the Data Scientist Internship:

• Research, design, develop, and implement data driven solutions using machine learning technologies and advanced statistical methods
• Full life cycle machine learning development from selecting model objective to model deployment and maintenance
• Utilize advanced statistical skills to analyze and understand complex data, curate features, and identify targets
• Directly engage with end users and business stakeholders to turn ambiguous requests into measurable objectives
• Evaluate model performance and the value our systems are delivering to the end user. Understand how users will interact with your models and systems
• Work with large datasets that require cloud resources or distributed computing. Work with data that is dirty, high dimensional, sparse, and imbalanced
• Design machine learning algorithms for problem solving, which may include data cleaning, feature selection, statistical modeling, data clustering and classification, text processing, and other machine learning techniques, to solve complex healthcare problems presented by healthcare organizations

• Work as a key part of cross-functional teams with various internal customer groups to study quantified business cases, identify business problems and formulate desired outcomes

Key Qualifications and Experience:

• Currently in the process of obtaining a degree in computer science or related quantitative field
• Candidates who have completed their degree in the last six months are also encouraged to apply
• Significant course work, professional, or research experience in building diverse machine learning solutions
• Exploratory data analysis experience that demonstrates statistical knowledge
• Ability to develop prototypes by manipulating and analyzing complex, high-volume, high-dimensionality data from various sources
• Demonstrated ability to create SQL queries, analyze large amounts of data, create visualizations, and interpret qualitative data (research and feedback) and incorporate into analyses
• Demonstrated ability to work with business partners to understand their problems and develop technical solutions
• Proficient programming in both Python and query languages (e.g., SQL, pySpark)
• Experience with machine learning frameworks (e.g, TensorFlow, scikit-learn, NumPy, XGBoost, TensorFlow, PyTorch, NLTK, etc.)
• Demonstrated ability to understand a complex business domain and strong interest in healthcare
• Required minimum cumulative undergraduate GPA of 3.0

The following skills/experiences/knowledge, a plus:

• Pursuing MS or PhD in computer science or quantitative field with a focus in Machine Learning
• Expertise in one or more of the following AI specializations: natural language processing, personalization, information retrieval, recommendation systems, or knowledge bases
• Experience and/or motivation to work on modern deep learning approaches
• Knowledge of or experience in building production quality and large-scale deployment of applications related to AI, data science and machine learning
• Demonstrated knowledge of health plan operations, medical terminologies/ontologies and/or clinical informatics and healthcare systems
• General software development skills (source code management, debugging, testing, deployment, etc.)

The hourly rate for this job profile is between $25 - $45.

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. Information about how Cambia Health Solutions collects, uses, and discloses information is available in our Privacy Policy. As a health care company, we are committed to the health of our communities and employees during the COVID-19 pandemic. Please review the policy on our Careers site.

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