About Mansi
Microsoft Certified Data Science professional with extensive experience in computer science, advanced analytics, statistical model building, machine learning algorithms, and also worked as a professor in the Engineering Institute in the Information Technology department.
Expertise in Machine Learning domains such as predictive analysis and computer vision. Good at solving modern problems with AI and deep learning using Python frameworks such as TensorFlow, Scikit-learn and Keras.
English
Native or bilingual
Spanish
Basic
Gujarati
Native or bilingual
Hindi
Fluent
Remote only
Primarily works remotely
Experience
- IMARTICUS LEARNING, AHMEDABAD, INDIADATA SCIENCE TRAINERTECHNovember 2019 - December 2019 (2 months)Ahmedabad, IndiaTrained data science students on R language, predictive analytics and machine learning algorithms and ensured that they understand data science in-depth.
- NEAL ANALYTICS PVT. LTD.DATA SCIENTISTTECHMay 2018 - November 2018 (6 months)Pune, IndiaPredictive analytics in Oil & Gas using R studio. Advanced analytics to ensure efficient performance ofoil drilling machine.Developed predictive models to analyse the oil drilling machine parts failure and its frequency.Carried out exploratory data analysis. Created multi class classification/classifier models. Comparison of multiple models like K-NN, Random Forest & gbm. Validation of the model for its effectiveness
- KLOUDDATA LABS PVT. LTDDATA SCIENTISTTECHJune 2016 - April 2018 (1 year and 10 months)Pune, IndiaPredictive analytics in healthcare using R &Knime / PMMLAdvanced analytics-based healthcare product design using machine learning and predictive analytics to help healthcare organizations to optimize staffing and patient readmission by predicting inflow and length of stay.Used machine learning algorithms like multivariate regression and logistics regression that can identify patients with traits that produce a high impact on the likelihood of readmission can give providers an extra indication of when to focus resources on follow-up and how to design discharge planning protocols to prevent speedy returns to the hospital.Predictive analytics in Supply chain management using R studio.Collected and analysed procurement data to form meaningful insights and aid effective business decision making.Created predictive models on vendor performance KPIs like demand vs. supply, a delivery performance which includes lead time and accuracy, return and quality rejection rate, and procurement cycle time analysis. Extensively used machine learning algorithms like a random forest and decision tree.Awards at Klouddata – Shining Star Award, Kloudie of the Month
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Education
- MASTER IN ARTIFICIAL INTELLIGENCE & DEEP LEARNINGUNIVERSIDAD DE ALCALÁ (UAH)2022This course provided a complete review of Artificial Intelligence and Deep Learning and their applications in Businesses and the Industry. Learned implementation of the different algorithms in high-level languages: (Python) in order to solve real problems as well as to understand the difficulties in implementing such algorithms in practice. Proposed solutions based on Machine Learning from a broad perspective, considering the ethical and legal aspects and the economic and social implications of the automation of the processes in the businesses. THESIS - Chest X-Ray Image Classification using Transfer Learning with Convolutional Neural Networks. The objective of the thesis was to evaluate the performance of a transfer learning system based on Convolutional Neural Networks on medical images.
- MASTER OF TECHNOLOGY (M.TECH) - COMPUTER ENGINEERINGCHAROTAR UNIVERSITY OF SCIENCE & TECHNOLOGY2013
Certifications
- 70-773: ANALYZING BIG DATA WITH MICROSOFT RMicrosoft2018