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Data Sciences - Current Opportunities

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Knowledge Graph, Data Scientist

At Bangalore
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Company Profile:

Mango Sciences is an AI driven data aggregation and analytical engine providing end-to-end hospital-based analytics focusing on operational efficiencies and quality of care. With this capability, Mango Sciences is currently embedded in more than 350 different hospitals & clinics covering ~ 28 million lives in India.

Mango Sciences has ambitious plans to continue investing and building healthcare capacity across Africa and South Asia. This encompasses the dual mission of serving the healthcare needs of the population by improving the population’s access to quality healthcare, whilst catalysing engagement with Life Science Companies. The objective is to build a longitudinal patient record, from a patient’s DNA, all the way to their consumption and shopping habits across India and emerging markets. Our aim is to unlock insights into human populations never studied before with the power of data.

Working at Mango Sciences means being entrepreneurial, thinking big, and working together to make the impossible a reality. We are inspired by the things that seem impossible. At Mango Sciences, we see the impact of our collective ideas and expertise, and the power of science to deliver them.

We know that meaningful results require not only the right approach but also the right people. We invite you to reimagine healthcare with us. You will have the opportunity to play an important role in helping our clients drive healthcare forward and ultimately expand access to healthcare and improve patient health outcomes.

Position Summary:

To deliver on our mission of improving healthcare access and quality, we are looking for an experienced Knowledge Graph Data Scientist to join our small, fast-growing team.

The Knowledge Graph Data Scientist serves on a project team that leverages our industry-leading healthcare data to deliver clinical insights in engagements with healthcare providers and Life Sciences Companies. In this role, he/she will be part of an agile data science team, with the excitement, pace, and development opportunities that come with working in an early-stage company.

Position Responsibilities:

  • You will be part of a high-impact team leveraging and optimising a Knowledge Graph (KG) based on Mango’s proprietary healthcare data.
  • Develop, incorporate, and refine all parts of the KG-related pipeline – knowledge storage and representation, relevant data sources, visualisation tools, embeddings, and clinical prediction models.
  • Utilise the latest techniques to generate robust embeddings and apply deep/machine learning in the context of KG’s.
  • Contribute to problem solving discussions by clearly defining the issues and offering solutions.
  • Provide timely updates to the management and leadership teams.

Position Requirements:

  • A degree in Data Science, Computer Science, Statistics, or a related field of study.
  • 3-5 years of KG-specific work experience, demonstrated to be:
    • An experienced practitioner of machine learning in the context of KG’s.
    • Up to date with recent developments in machine learning (ML) and are familiar with current trends in the wider ML community and KG’s.
  • Strong scripting and programming skills in Python (required) and at least one KG industry standard, e.g., SPARQL.
  • Experience with KG platform and graph database management tools, e.g., Neo4j.
  • Healthcare industry knowledge (medical and pharmaceutical) is preferred.
  • Experience in building models from scratch and working with structured and unstructured data.
  • Excellent communication (written and verbal), interpersonal skills, and the ability to foster collective partnerships.

Other Skills:

  • Dedication to teamwork with a demonstrated ability to collaborate across functions.
  • Track record of innovation with the vision and entrepreneurial spirit to take on a key role in a small, fast-growing company.


  • Commitment to Excellence
  • Do GREAT Attitude
  • Honesty & Integrity
  • Perseverance
  • Respect

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