Optum is a global organization that leverages technology to provide care, helping millions lead healthier lives. Working with our team will have a direct impact on improving health outcomes by connecting individuals to essential care, pharmacy benefits, data, and resources, helping them feel their best. We foster a culture of diversity, inclusion, talented colleagues, comprehensive benefits, and career growth opportunities. Make a difference in the communities we serve as we work to advance health equity on a global level. Join us to Care. Connect. Grow together.
Key Responsibilities:
- Conduct offline/online analysis of large datasets using Hadoop ecosystem tools
- Engage with big data technologies and prototype solutions to enhance data processing and analytics architecture
- Identify and resolve project issues through effective communication
- Manage multiple healthcare-related projects simultaneously
- Maintain a cooperative, team-oriented approach
- Assist clients in making informed decisions based on their needs
- Adhere to company policies and directives, which may include shifts in work location, team assignments, or flexible work arrangements, as the business environment evolves
Qualifications:
- Undergraduate degree or equivalent experience
- Proficiency in R, Python, or Spark (Mlib)
- Experience with Machine Learning algorithms, including Linear & Logistic Regression, Time Series Analysis, Support Vector Machine, K-Means Clustering, K-Nearest Neighbors, Decision Trees, Random Forest, Naive Bayes, PCA, SVD, Artificial Neural Networks, Association Rules, Genetic Algorithm, Optimization, and Boosting techniques
- Familiarity with tools like SQL and Excel
- Strong understanding of data structures, schema, data modeling, machine learning, and optimizing big data processes
- Ability to leverage machine learning or AI to create innovative solutions
- Excellent communication, analytical, problem-solving, and decision-making skills
Locations: Noida, India
Salary Package:- As per Company Standards
Apply Link:- Click Here To Apply (Apply before the link expires)
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