Akshat Anand

Software Engineer

Pune, Maharashtra, India4 yrs 2 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in Java and Spring Boot for scalable applications.
Led successful migration projects in Fintech.
Recognized for excellence in machine learning initiatives.

Stackforce AI infers this person is a Fintech Software Developer with expertise in scalable systems and machine learning.

Contact

Skills

Core Skills

JavaSpring BootMachine LearningData Science

Other Skills

Batch ProcessingBlockchainC (Programming Language)C++CI/CDCascading Style Sheets (CSS)Cloud IntegrationConfluenceData AnalysisData MappingGitGitHubHTMLJavaScriptJenkins

About

As a Software Developer with a focus on building scalable and high-performance distributed systems, I leverage my expertise in Java and Spring Boot to develop robust, enterprise-grade applications. With a passion for clean code, system architecture, and solving complex challenges, I am dedicated to creating solutions that scale efficiently. I thrive in collaborative environments and enjoy working on projects that push the boundaries of technology, ensuring that performance, reliability, and user experience are always at the forefront.

Experience

4 yrs 2 mos

Total Experience

2 yrs 1 mo

Average Tenure

3 yrs 10 mos

Current Experience

Barclays

2 roles

Software Engineer (BA-4)

Mar 2025 – Present · 1 yr 3 mos · Pune, Maharashtra, India

Promoted to BA4 Developer in Barclays Financial Assistance (BFA) Technology team for delivering impactful work across the team.
Took ownership from a data perspective of migrating products like loans and cards from legacy systems to a third-party Collection system, ensuring seamless data transition while adhering to agile methodologies.

Software Engineer (BA-3)

Aug 2022 – Mar 2025 · 2 yrs 7 mos · Pune, Maharashtra, India

Developer in Barclays Financial Assistance (BFA) Technology team, involved in migrating from legacy to third-party Collection system via cloud integration, supporting 10,000+ monthly customer accounts in financial difficulty with a nightly batch process.
Designed batch orchestration and Java-based API/file transfer interfaces, handling 5,000 daily transactions, aiding downstream teams in Collections and Recovery data mapping for reporting.
Enhanced system governance with SOX controls, cutting compliance risks by 30% and ensuring audit-ready reliability.
Automated CI/CD pipelines with Jenkins, speeding up deployments by 25%, and improved code quality via JUnit TestCases, achieving 85% Sonar coverage and zero critical Veracode scan issues.
Optimised data workflows with error-handling, reducing mapping discrepancies by 15% for downstream financial recovery reporting teams.
Mentored junior developers in Java, CI/CD, and code quality practices, promoting continuous learning within the BFA Technology team.
Earned 41+ recognitions from directors, CIOs, and cross-functional teams for impactful system modernisation and operational efficiency contributions.

JavaSpring BootCloud IntegrationCI/CDJenkinsSOX Controls+2

Samsung electronics

Samsung Prism Developer

Jul 2021 – Nov 2021 · 4 mos · Chennai, Tamil Nadu, India

Developed Mood Prediction Network in collaboration with Samsung Research Institute Bangalore (SRI-B), integrating multiple sensors.
Led all stages from conceptualisation to deployment, ensuring alignment with project objectives.
Employed advanced machine learning techniques for model training and validation.
Achieved accurate mood prediction over specific durations through rigorous testing and sensor fusion, recognized with a Certificate for Excellence.
Received Best Paper Award at IEEE Connect 2022, 8th International Conference on Electronics, Computing, and Communication Technologies.

Machine LearningSensor FusionModel TrainingData Analysis

Studentcode-in

Project Lead and Mentor

May 2020 – Sep 2020 · 4 mos · Remote

Led as Project Lead at Student Code-in (June 2020 - August 2020), guiding newcomers in open-source data science and machine learning projects.
Mentored contributors on creating issues, merging pull requests, and using tools like Python, TensorFlow, and Pandas.
Facilitated the development of ML models, data pipelines, and analytics solutions with best practices.
Fostered a collaborative community, emphasising teamwork and reproducible workflows in data science.
Earned a Certificate of Appreciation for outstanding contributions as a Project Admin in 2020.

PythonTensorFlowPandasData Science

Aidlife

Data Science Intern

May 2020 – Jul 2020 · 2 mos

Collaborated with the R&D team to optimize emergency response solutions by leveraging machine learning algorithms for improved decision-making.
Collected and curated feasible datasets to identify patterns in emergencies, enabling accurate predictions and actionable insights.
Developed models to predict emergency severity based on location, enhancing response prioritization and resource allocation.

Machine LearningData Analysis