Sr. Data Scientist – Healthcare

Overview

At Anblicks, we enable enterprises to modernize their data landscape through Data Engineering, Cloud, and AI-driven solutions. We partner with global organizations to design scalable data platforms and build intelligent analytics products that deliver measurable business impact.

We are seeking a Sr. Data Scientist – Healthcare to join our Data Science & AI practice. This is a hands-on role focused on designing, developing, and deploying advanced machine learning solutions within the healthcare domain. The ideal candidate will bring strong modeling expertise, healthcare domain knowledge, and experience working in cloud-based data ecosystems.

Role Overview

As a Sr. Data Scientist at Anblicks, you will:

• • Develop high-performance ML models for healthcare use cases.
  • Collaborate with product, engineering, and business teams.
  • Contribute to scalable healthcare data products.
  • Ensure compliance, governance, and high-quality model performance.
  • Drive adoption of modern AI/ML technologies.
    

• • Combine healthcare domain expertise with AI/ML techniques to develop predictive and prescriptive models.
  • Apply advanced statistical and machine learning algorithms (GLM, Decision Trees, Boosting, Bagging, SVM, Regression, Clustering, etc.).
  • Perform model training, hyperparameter tuning, validation, and performance evaluation.
  • Support validation, enhancement, and optimization of existing healthcare data products.
  • Contribute to experimentation with new modeling techniques and algorithms.
    

• • Collaborate with product managers and stakeholders to define business requirements and modeling approaches.
  • Identify relevant KPIs to measure product performance and business impact.
  • Work closely with data engineering and platform teams to productionize ML models.
  • Contribute to scalable ETL pipelines and data transformation workflows.
  • Suggest automation and continuous improvement initiatives.
  • Support closed-loop measurement and outcome tracking solutions.
    

• • Monitor model performance and make improvements as required.
  • Maintain and enhance existing models and analytical products.
  • Ensure compliance with healthcare data regulations (e.g., HIPAA).
  • Support governance and QA processes across healthcare data assets.
    

• • 5–7 years of experience in Data Science, Machine Learning, or Advanced Analytics.
  • 3+ years of experience working with healthcare data and healthcare use cases.
  • Strong analytical skills with experience handling large and diverse datasets.
  • Hands-on expertise in ML algorithms and statistical modeling techniques.
  • Strong knowledge of model evaluation methods and hyperparameter tuning.
  • Experience deploying ML models into production environments.
  • Experience building ETL pipelines and data transformation workflows.
  • Experience working in Big Data or Cloud platforms such as AWS, Snowflake, Databricks, or similar ecosystems.
  • Proficiency in Python, R, Scala, Spark/PySpark, H2O, or similar tools.
  • Strong communication skills with the ability to explain complex technical concepts to business stakeholders.
  • Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or related quantitative field.
    

• • Experience with Deep Learning and Neural Network frameworks.
  • Knowledge of containerized model deployment (Docker, Kubernetes).
  • Experience with orchestration tools such as Airflow or Kubeflow.
  • Experience in consulting-led healthcare analytics engagements.
  • Master’s degree in Data Science, Statistics, Applied Mathematics, Engineering, or related field.
  • Experience with H2O or similar machine learning platforms.
    

• • Work on advanced healthcare AI and analytics programs.
  • Collaborate with global enterprise clients.
  • Exposure to modern cloud-native data ecosystems.
  • Be part of a fast-growing Data & AI practice.
  • Opportunity to build impactful, scalable healthcare solutions.