Anshul Tak

Software Engineer

South Delhi, Delhi, India3 yrs 3 mos experience

Most Likely To Switch

Key Highlights

Developed secure authentication systems for scalable applications.
Implemented quantitative finance models for risk analysis.
Integrated payment gateways ensuring seamless transactions.

Stackforce AI infers this person is a Backend Developer with expertise in Fintech and SaaS solutions.

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Skills

Core Skills

Back-end Web DevelopmentAuthentication SystemsPaymentsQuantitative FinanceRisk Management

Other Skills

AlgorithmsAmazon DynamodbAmazon Web Services (AWS)AthenaC++DartData AnalysisData StructuresDatabasesGo (Programming Language)JavaKubernetesNotificationProgrammingProgramming Languages

About

I am deeply passionate about computers, programming, and science. I am intrigued by the increasing capabilities of computers across various fields. I enjoy building systems and structures, particularly those that contribute meaningfully to society as a whole.

Experience

Juleo

Software Developer

Jan 2024 – Present · 2 yrs 2 mos · Gurugram, Haryana, India · On-site

1. Developed a secure, scalable authentication service for different types of authentication used in production .
2. Proposed and implemented a backend driven server-centric model, resulting in an 10% decrement in app’s size and 60% reduction in app updates.
3. Integrated a robust payment gateway integration with Razorpay, ensuring seamless transaction processing and minimizing errors.

Authentication SystemsPaymentsBack-End Web DevelopmentGo (Programming Language)dockerKubernetes+2

Natwest group

Risk Analyst

May 2022 – Jul 2022 · 2 mos · Gurugram, Haryana, India · Hybrid

1. Implemented the methodology of estimation, simulation, and validation of the AR1 model on risk factor
2. Validate the NSS smoothing low impact on calibrated volatility which is sigma in the AR1 model
3. Applied BIN test to PITs value and compared the PITs values for different weekdays, percentile change, and currencies, validated that PITs did not vary significantly for each scenario
4. Compare the PITs values of any two-year quarter using the PITs distribution analysis, with RF Table for analysis of exception count for two separate fixed above and below percentiles and a frequency plot that closely resembles our binomial distribution.

Quantitative ResearchQuantitative AnalyticsData AnalysisQuantitative FinanceRisk Management