Harsha Hanamshet

Data professional with expertise in Python, SQL, Generative AI (GenAI), machine learning, data visualization, and statistical analysis. Strong academic foundation in mathematics, probability, statistics, and linear algebra with experience building analytical solutions, predictive models, AI workflows, and automation systems that improve data quality, operational efficiency, and business decision-making. Skilled in transforming raw data into actionable insights through machine learning, reporting, and process optimization.

Mathematics Instructor – CSE Department at NxtWave Disruptive Technologies (2025-07 – Present)

• Delivered mathematics lectures integrated with computing concepts for engineering students.
• Designed and taught modules covering probability, statistics, linear algebra, logic operators, algorithms, and discrete mathematics.
• Developed interactive learning materials and digital resources to strengthen analytical and computational problemsolving.
• Applied real-world examples and data-driven teaching methods to improve student understanding of statistical and mathematical concepts.
• Collaborated with faculty members and industry mentors to align curriculum with industry requirements.
• Evaluated student performance using structured assessments, feedback analysis, and progress tracking. (PowerBi)

Mathematics Trainee Instructor at NxtWave Disruptive Technologies (2025-05 – 2025-07)

• Conducted engaging sessions on logic operators, number systems, probability, and applied mathematics for computer science learners.
• Improved student outcomes by using interactive and analytics-backed teaching methodologies.
• Observed senior educators and implemented feedback-driven improvements in content delivery.
• Created simplified explanations and problem-solving frameworks for technical mathematical topics.

AI Mathematics Expert at Remotasks (2023-10 – 2024-05)

• Trained more than 20 AI models and GenAI features to improve mathematical reasoning and factual accuracy.
• Audited and refined over 700 AI-generated outputs, increasing response accuracy and relevance by 15%.
• Developed internal AI training protocols that improved process efficiency by 20%.
• Applied probability, statistical validation, and data quality metrics to evaluate and optimize model responses.
• Collaborated with cross-functional teams to improve AI output consistency and reduce error rates.

Managed Network Expert at Chegg India (2023-03 – 2023-04)

• Designed and optimized network setups for more than 20 clients, reducing downtime by 25%.
• Delivered academic and technical support with 99% data accuracy, improving student query resolution rates.
• Implemented automation strategies to streamline operational reporting and performance tracking.
• Analyzed system performance data to identify inefficiencies and improve network reliability.

M.Sc. in Mathematics & Statistics – K.L.E. Society's R.L. Science Institute (2023-12)