Senior Data Scientist (ML)

Company

hirify.global Group is the world's largest healthcare platform connecting patients with doctors via SaaS and AI tools.

What you will do

• Own and deliver end-to-end data science and BI projects from exploration and experimentation to production deployment.
• Build predictive models and machine learning solutions to support business decision-making and operational efficiency.
• Analyze large datasets to uncover actionable insights, trends, and growth opportunities.
• Design and evaluate A/B tests to measure impact and validate hypotheses.
• Collaborate with cross-functional teams across Product, Sales, Marketing, and Engineering.
• Improve and maintain scalable data pipelines and ML workflows.

Requirements

• 5+ years of experience in Data Science, Machine Learning, or Advanced Analytics.
• Strong Python skills and hands-on experience with Pandas, Scikit-learn, TensorFlow, or PyTorch.
• Solid understanding of statistics, experimentation, and model evaluation techniques.
• Experience with SQL and data warehouses such as Redshift, BigQuery, or Snowflake.
• Familiarity with MLOps and modern development practices (Git, Docker, MLflow, CI/CD).
• Must already have the legal right to work in the country of residence or the location of the role.

Nice to have

• Experience with Airflow, Kubernetes, Jupyter Notebook, or Athena.
• Knowledge of NLP, LLMs, or AI agent workflows.
• Familiarity with BI and visualization tools like Tableau or Superset.
• Previous experience in SaaS or high-growth tech environments.

Culture & Benefits

• Global healthcare insurance and mental health support.
• Wellness benefits, including gym memberships.
• Flexible work hours and remote work options.
• Local perks such as meal vouchers and transport allowances depending on the location.
• Opportunities for career growth and cross-functional project exploration.

Hiring process

• Introductory chat with a Talent Partner.
• Interview with the Business Intelligence Manager.
• Take-home business case and a collaborative discussion on findings.
• Final interview with a global stakeholder.