Data Scientist (Machine Learning) (Onsite, Hebbal)

We are seeking a Data Scientist – ML with hands-on experience in building and deploying data-driven solutions.

You will work closely with cross-functional teams to extract insights, develop machine learning models, and deploy scalable analytics solutions across various cloud platforms. As a Data Scientist – ML, you’ll play a key role in harnessing data to drive better outcomes, improve performance, and enhance the lives of those served by our clients.

Key Responsibilities:

• Design and implement predictive models and machine learning algorithms to solve healthcare-specific challenges
• Analyze large, complex healthcare datasets including electronic health records (EHR) and claims data
• Develop statistical models for patient risk stratification, treatment optimization, population health management, and revenue cycle optimization
• Build models for clinical decision support, patient outcome prediction, care quality improvement, and revenue cycle optimization
• Create and maintain automated data pipelines for real-time analytics and reporting
• Work with healthcare data standards (HL7 FHIR, ICD-10, CPT, SNOMED CT) and ensure regulatory compliance
• Develop and deploy models in cloud environments while creating visualizations for stakeholders
• Present findings and recommendations to cross-functional teams including clinicians, product managers, and executives
  
  

Qualifications Required:

• At least 2 years of hands-on experience in data science, analytics, or machine learning roles
• Demonstrated experience working with large datasets and statistical modeling
• Proficiency in Python , Python Anaconda library for data analysis and machine learning
• Experience with SQL and database management systems
• Experience with ML and Deep Learning frameworks using one or more of TensorFlow, PyTorch, Keras, scikit-learn, MLFlow, Kubeflow.
• Familiarity with data visualization tools such as Tableau, Power BI, matplotlib, ggplot2
• Experience with version control systems (Git) and collaborative development practices
• Strong foundation in statistics, hypothesis testing, and experimental design
• Experience with supervised and unsupervised learning techniques
• Knowledge of data preprocessing, feature engineering, and model validation
• Understanding of A/B testing and causal inference methods
• Experience with cloud platforms and big data technologies such as Spark, Hadoop
  
  

What You’ll Need to Be Successful (Required Skills):

• Advanced Algorithm Implementation: At least 1-2 years of experience implementing and optimizing machine learning algorithms from scratch, including deep understanding of algorithmic complexity, hyperparameter tuning, and performance optimization techniques
• Model Pipeline Development: Proficiency in designing and building end-to-end ML pipelines including data ingestion, feature engineering, model training, validation, and deployment using tools like Apache Airflow, Kubeflow, or MLflow
• Cross-Validation and Model Selection: Experience with advanced model validation techniques including k-fold cross-validation, stratified sampling, time series validation, and ensemble methods for robust model selection and performance estimation
• Feature Engineering and Selection: Deep knowledge of feature engineering techniques including dimensionality reduction (PCA, t-SNE, UMAP), feature selection methods, and automated feature engineering approaches for improving model performance
• Model Interpretability and Explainability: Experience with model interpretation techniques such as SHAP, LIME, permutation importance, and other explainable AI methods to understand and communicate model decision-making processes
• Deep Learning Architectures: Familiarity with designing and implementing custom neural network architectures including CNNs, RNNs, Transformers, and experience with transfer learning and model fine-tuning techniques
• MLOps and Model Monitoring: Understanding of machine learning operations including automated model retraining, drift detection, A/B testing for ML models, and continuous integration/continuous deployment (CI/CD) practices for ML systems
  
  

Education/ Certifications:

• Bachelor’s or master’s degree in computer science, Data Science, Statistics, Engineering, or a related field.
  
  

Preferred Skills:

• At least 1 year of experience working with healthcare data or in healthcare IT environments
• Familiarity with electronic health record (EHR) systems and healthcare workflows
• Understanding of healthcare data privacy regulations (HIPAA, HITECH)
• Knowledge of clinical data standards and interoperability frameworks
• Knowledge of MLOps practices and model deployment pipelines
• Familiarity with natural language processing for clinical text analysis
• Experience with time series analysis for patient monitoring data
  
  

Why Join Us?

At Netsmart you’ll work on exciting challenges that shape the future of healthcare.

You’ll have the opportunity to:

• Collaborate with talented professionals passionate about technology.
• Work in a supportive and inclusive environment where your growth is prioritized.
• Access professional development opportunities, including certifications and training.
• Enjoy a competitive compensation package and comprehensive benefits.
  
  

Netsmart is proud to be an equal opportunity workplace and is an affirmative action employer, providing equal employment and advancement opportunities to all individuals. We celebrate diversity and are committed to creating an inclusive environment for all associates. All employment decisions at Netsmart, including but not limited to recruiting, hiring, promotion and transfer, are based on performance, qualifications, abilities, education and experience. Netsmart does not discriminate in employment opportunities or practices based on race, color, religion, sex (including pregnancy), sexual orientation, gender identity or expression, national origin, age, physical or mental disability, past or present military service, or any other status protected by the laws or regulations in the locations where we operate.

Netsmart desires to provide a healthy and safe workplace and, as a government contractor, Netsmart is committed to maintaining a drug-free workplace in accordance with applicable federal law. Pursuant to Netsmart policy, all post-offer candidates are required to successfully complete a pre-employment background check, which is provided at Netsmart’s sole expense.