Soumy Ladha

Software Engineer

Cambridge, Massachusetts, United States6 yrs 11 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Developed scalable RESTful APIs at Goldman Sachs.
Engineered data pipelines improving data quality and performance.
Achieved significant cost savings through machine learning models.

Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in Fintech and Data Engineering.

Contact

soumyladdha@gmail.com LinkedIn

Skills

Core Skills

Backend DevelopmentApi DevelopmentData EngineeringMachine LearningData Science

Other Skills

AWS CloudFormationAWS LambdaAmazon CloudWatchAmazon DynamodbAmazon EC2Amazon S3Amazon Simple Notification Service (SNS)Amazon Web Services (AWS)Anomaly DetectionApache SparkBlack-ScholesCloud ComputingCompilersData AnalyticsData Quality

About

I am a graduate student in computer science at the University of Chicago. I've spent the last 3.5 years working on backend applications and systems, particularly on core application logic, databases, data and application integration, APIs, and pipelining. I am fluent in numerous programming languages, including Java, C, Python, and Kotlin, as well as frameworks like Springboot, RxJava, CUnit, and Junit. I've worked with Spark, Hadoop, MongoDB, Elasticsearch, and Postgres, among other platforms. My most significant contribution to Goldman Sachs has been the development of RESTful APIs and Big Data pipelines for CRUD operations, with a strong emphasis on scalability, responsiveness, and data quality. I've worked on developing end-to-end pipelines that include checks for data consistency and anomaly, as well as efficient in-memory transformations that may be stored in a non-relational database. Finally, creating reactive APIs to enhance requests per thread, resulting in improved performance and efficiency. If you are interested in grabbing a coffee and talking about software engineering, machine learning, or any other fruitful conversation, shoot me an email or send a message. I will be pleased to connect.

Experience

6 yrs 11 mos

Total Experience

3 yrs 5 mos

Average Tenure

3 yrs 10 mos

Current Experience

Audible

Software Development Engineer II

Aug 2022 – Present · 3 yrs 10 mos

Improved existing alarms to proactively detect latency and error API across multiple downstream services
Implemented elastic search template to enhance experience when user accesses their Library
Developed new API to provide keyword suggestion related to a search term thereby improving user search journey
Developed real world traffic simulator to dry and load test various scenarios in a coordinated way to test elasticity and scalability of our APIs. Subsequently tested by coordinating with multiple teams to quantify the impact of prime day and black Friday
Wrote a COE for customer impacted issue which resulted in monetary loss and degraded user experience. Created 7 action items which would further improve our services and prevent similar kind of incident happening in the future.

ElasticSearchAPI DevelopmentLatency DetectionBackend Development

Goldman sachs

3 roles

Associate Software Engineer

Jan 2021 – Aug 2021 · 7 mos

Built reactive REST APIs to enhance performance by 20%, allowing us to provide services like push alerts, user preferences, badges, and news feeds, similar to those seen on social networking platforms.
Engineered social network suggester that captures interaction data, does interaction analytics, and builds pipelines to deliver suitable suggestions, resulting in a 70 percent increase in DAU and MAU for the platform.
Developed admin API's to bulk upload user data, preferences and connections thus solving cold start problem.

REST APIsPerformance OptimizationData AnalyticsBackend DevelopmentAPI Development

Software Engineer

Aug 2020 – Jan 2021 · 5 mos

⦁ Added an anomaly detection package to ETL pipelines to discover data quality issues and determine the root cause.
⦁ Built multi-threaded non-blocking data pipelines to boost requests per thread for persisting live news across 200K companies, 500K expertise & badges, and 35K employee client coverage while keeping all updates in transactional mode.
⦁ Implemented ETL to process 25 million daily records while milestoning and auditing modifications to retrospectively update the delayed or modified records, resulting in the creation of a warehouse to store analytical data.

ETLAnomaly DetectionData QualityData EngineeringBackend Development

Machine Learning Engineer

Jun 2018 – Jul 2020 · 2 yrs 1 mo

⦁ Developed NLP based text classification model for tagging receipts to the business unit via token extraction resulting in $500,000 annualised savings and workflow improvement of about 40%.
⦁ Built unsupervised Multidimensional Anomaly detection, to identify the pattern and point changes with support for hierarchical data. The model had a false error removal rate of 90% while a root cause identification rate of 85%

NLPMachine LearningAnomaly DetectionData Science

Aurigin

Machine Learning Researcher

May 2017 – Jul 2017 · 2 mos · Bangalore Urban, Karnataka, India · On-site

⦁ Built a Heteroskedastic time series model GARCH to predict appreciation of Real Estate in 50 cities in U.S with 76% accuracy
⦁ Designed a Machine Learning model to predict capital-raising by a company using XGBoost thus achieved an accuracy of 82%

Time Series AnalysisMachine Learning