About nference
At nference, the “Google of Biomedicine,” we are making the world’s biomedical knowledge computable to power quantum leaps in human health. By partnering with elite medical institutions, we transform massive, unstructured datasets-including clinical notes, lab results, and medical images-into a structured, research-ready ecosystem. Leveraging state-of-the-art AI and high-performance computing, we bridge the gap between clinical phenotypes and molecular genotypes to accelerate the discovery of next-generation diagnostics and personalized treatments.
Requirements
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Pursuing a Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field, with an expected graduation year of 2026 or 2027.
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Strong understanding of SQL for querying, joining, filtering, and aggregating data across multiple tables.
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Hands-on experience with Python (especially pandas and NumPy) through coursework, internships, or academic/personal projects.
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Good understanding of descriptive and diagnostic analysis, with the ability to interpret data and derive meaningful insights.
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Experience working with structured or semi-structured datasets, including data cleaning, transformation, and validation.
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Ability to break down business or analytical problems into logical, manageable steps.
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Basic understanding of data visualization principles, with experience creating dashboards or reports using Excel, Power BI, Tableau, or similar tools.
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Interest in automating repetitive data analysis and reporting tasks using SQL or Python.
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Strong analytical thinking, attention to detail, and problem-solving skills.
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Good written and verbal communication skills, with the ability to present findings clearly.
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Willingness to learn new analytical tools, technologies, and best practices in data analysis.
Good to Have (Optional)
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Familiarity with notebook-based workflows such as Jupyter Notebook or Google Colab.
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Exposure to large datasets, distributed data processing concepts, or basic statistical and predictive analysis through academic projects.
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Participation in hackathons, research projects, Kaggle competitions, or open-source data projects.
Responsibilities
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Apply foundational knowledge of SQL, Python, and data analysis techniques to solve analytical problems and generate accurate insights.
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Query, clean, transform, and validate data from multiple sources to create analysis-ready datasets.
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Perform descriptive and diagnostic analysis to identify trends, patterns, anomalies, and actionable insights.
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Support data validation and quality assurance by identifying inconsistencies, missing values, and logical issues in datasets.
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Create dashboards, reports, and visualizations that effectively communicate analytical findings to stakeholders.
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Collaborate with mentors and cross-functional teams to understand business requirements and translate them into analytical tasks.
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Document analytical methodologies, assumptions, and findings to ensure clarity, reproducibility, and knowledge sharing.
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Assist in automating recurring data extraction, validation, and reporting processes using SQL and Python.
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Gain exposure to data pipelines, scalable data processing concepts, and modern analytics workflows.
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Continuously develop technical and analytical skills by learning new tools, techniques, and industry best practices while contributing to team initiatives.
