Maniteja Nandana
Senior Software Engineer at Microsoft
Hyderabad, Telangana, India
Summary
👤
Senior🎓
Top SchoolManiteja Nandana is a senior software engineer with 11 years of experience building scalable, compliance-focused systems and classification services, currently contributing to Microsoft Purview. With a strong full-stack background from PayPal — spanning Java, React, Node, GraphQL and Oracle — he designs mid-tier REST APIs and data collection tools for regulatory tooling at scale. He combines industry production experience with research roots (DRDO) and internships at Amazon and BARC, bringing both applied ML and systems engineering to bear. An active open-source contributor, he has improved numerical reliability and ML functionality in flagship Python libraries such as SciPy and scikit-learn, including tests and fixes for statistical distributions and model utilities. Based in Hyderabad, he blends deep technical rigor with a research-oriented curiosity, often surfacing subtle correctness issues in mathematical code and documentation.
11 years of coding experience
9 years of employment as a software developer
BITS Pilani, Birla Institute of Technology and Science12th Standard, Mathematics, Physics and Chemistry, 12th Standard, Mathematics, Physics and Chemistry at Vijaya Ratna Junior College10th grade, Central Board of Secondary Education, 10th grade, Central Board of Secondary Education at Sri Vidya Secondary SchoolPrimary and High School, Central board of secondary education, Primary and High School, Central board of secondary education at V.P. Siddhartha Public School
English, Telugu, Hindi
Stackoverflow
36reputation
902reached
3answers
0questions
Github Skills (15)
testing10
data-analysis10
scikit-learn10
machine-learning10
scipy10
python10
scientific-computing10
data-science10
numpy10
scikit10
algorithms9
statistics9
pandas8
documentation7
random-forest6
Programming languages (3)
Github contributions (5)
scikit-learn/scikit-learn
Dec 2015 - Jul 2018
scikit-learn: machine learning in Python
Role in this project:
Data Scientist
Data ScientistContributions:12 commits, 25 PRs, 622 comments in 2 years 7 months
Contributions summary:Maniteja contributed significantly to the scikit-learn library by addressing issues related to machine learning model implementations and documentation. They implemented a fix enabling pandas input to the `log_loss` function, adding associated regression tests. Additionally, they clarified scoring parameters within the `LogisticRegressionCV` documentation and corrected errors in the `chebyshev` distance documentation. The user also implemented a meta-estimator for multi-output classification and added an indicator feature to the imputer output.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
scipy/scipy
Jan 2015 - Mar 2016
SciPy library main repository
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:18 commits, 19 PRs, 138 comments in 1 year 1 month
Contributions summary:Maniteja focused on improving the accuracy and reliability of statistical distributions within the SciPy library. They primarily updated and added new tests for distributions like Lomax, Rayleigh, and truncated exponential. Their contributions involved modifying existing test code and adding new test cases to ensure the correctness of the mathematical functions implemented in the library.
scipypythonscientific-computing
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