Abhijeet Panpaliya

Consultant

Bangalore Urban, Karnataka, India6 yrs 10 mos experience

Most Likely To Switch

Key Highlights

Strong foundation in Algorithms and Machine Learning.
Experience in quantitative development and strategy.
Proven track record in high-performance computing projects.

Stackforce AI infers this person is a skilled Software Engineer with expertise in Machine Learning and Quantitative Development.

Contact

ap@imc.com +919881764896 LinkedIn

Skills

Core Skills

AlgorithmsPython

Other Skills

Apache AirflowAssembly LanguageCC++Deep LearningElectronicsMachine LearningMicrosoft ExcelMicrosoft OfficeMicrosoft PowerPointMicrosoft WordNatural Language Processing (NLP)ProgrammingProject ManagementPython (Programming Language)

About

Software Engineer with a experience of working in the computer software industry. Skilled in C#, ML, NLP and Quant. Strong engineering professional with a Bachelor of Technology - BTech focused in Electrical and Electronics Engineering from Indian Institute of Technology, Madras.

Experience

6 yrs 10 mos

Total Experience

1 yr 5 mos

Average Tenure

2 yrs

Current Experience

Imc trading

Strategy Developer

Jun 2024 – Present · 2 yrs · Mumbai, Maharashtra, India · On-site

Strategy Team

Qnance research capital llp

Quantitative Developer

Nov 2021 – Jun 2024 · 2 yrs 7 mos · Bengaluru, Karnataka, India · On-site

AlgorithmsC++Python (Programming Language)Apache AirflowPython

Microsoft

Software Engineer

Jul 2020 – Nov 2021 · 1 yr 4 mos · Hyderabad, Telangana, India · Remote

Algorithms

Fidelity investments

Data Science Intern

May 2019 – Jul 2019 · 2 mos · Chennai Area, India

- Working on AI/ML use case of Automation of the process of Asset Listing over the Alternating Investments Portal

Centre for development of advanced computing (c-dac)

R&D Intern

Dec 2018 – Jan 2019 · 1 mo · Pune Area, India

Developed Software and Libraries for Matrix (Dense/Sparse) and Graph Computations in HPC -Data Environment.
Worked on performance and Integration of Dense, and Sparse Computations in Numerical Linear Algebra (NLA) Kernels using Object Programming approach ( based on C++, Python, and Fortran ) and Intel Mathematical Kernel Libraries (MKL) on large scale Intel Multi-Core Processor Systems.