Shiva Tejesh Rachamadugu

Senior Software Engineer

Lynnwood, Washington, United States10 yrs 3 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Reduced financial losses by over $14M annually.
Developed detection mechanisms for fraudulent activities.
Built a near real-time financial platform for accurate data.

Stackforce AI infers this person is a Fintech Software Engineer with expertise in fraud detection and data engineering.

Contact

Skills

Core Skills

Software EngineeringFraud DetectionData ScienceWeb DevelopmentData EngineeringMachine Learning

Other Skills

AlgorithmsCC++CollaborationCosine SimilarityData AnalysisData StructuresDistributed SystemsElasticSearchGo (Programming Language)JavaScriptKafkaMicrosoft OfficeNLPNaive Bayes Classifier

Experience

Airbnb

Senior Software Engineer

Jun 2021 – Present · 4 yrs 9 mos · Seattle, Washington, United States

Led multiple high impact projects in the Fraudulent Bad Debt domain, driving a reduction in annual financial losses from $20M+ to ~$6M, resulting in $14M+ in yearly savings.
Built content based detection mechanisms to identify and flag listings containing contact information in descriptions or images, aimed at preventing takeoff platform activity that increased the gross bookings by $100M+ annually.
Proactively identified and mitigated multiple complex financial fraud vectors by analyzing behavioral patterns and finding system loopholes. Designed and implemented detections and countermeasures.
Developed an ops driven review system to generate labeled datasets for ML training, bridging operations and data science. This enabled model development in detecting fraudulent activity and served as a key component of the overall mitigation strategy.
Designed and implemented payout delay mechanism for non-established hosts after proactively ideating and validating multiple mitigation strategies through in-depth data analysis, leading the team to adopt the payout delay as a core fraud mitigation approach.
Effectively collaborated with Product, Data Science, and external teams to drive alignment and deliver solutions in ambiguous, high impact problem spaces.

C++CPythonData StructuresDistributed SystemsAlgorithms+2

Uber

4 roles

Senior Software Engineer

Promoted

Jan 2020 – Mar 2021 · 1 yr 2 mos

Software Engineer II

Oct 2018 – Dec 2019 · 1 yr 2 mos

Software Engineer II

Sep 2017 – Sep 2018 · 1 yr

Software Engineer

Nov 2015 – Aug 2017 · 1 yr 9 mos

● Building a near Realtime Financial platform to provide 100% accurate aggregated level data without any losses and duplicates. Samza is used along with kafka as input stream and elasticsearch as final output data store.
● Worked on accounting Uber's revenue for each city and providing insights on the revenue trends. Used React, Node for the front-end and python tornado for the backend. Elastic search is being used for the data storage along with Uber's internal distributed stores.
● Developed a generic Rule Engine to facilitate change in business logic without changing the code.
● Developed a Web app using React and Node, which simplifies the process of sending weekly updates of projects in which people can subscribe to a project of their interest and get consolidated mail of project updates.
● Created an application for a Hackathon to display expenses of teams led by a manager, along with drill downs.

ReactNode.jsPythonElasticSearchKafkaSoftware Engineering+1

Directi

Software Engineer

Jun 2015 – Nov 2015 · 5 mos · Mumbai Area, India

Worked on developing a system to cluster similar News articles from various websites. Essential keywords of all articles were extracted using NLP and clustered articles using cosine similarity. Also classified individual article into two classes(Sensitive and Non-Sensitive) using Naive Bayes Classifier.

NLPCosine SimilarityNaive Bayes ClassifierMachine LearningSoftware Engineering

Qualcomm

Engineering Intern

May 2014 – Jul 2014 · 2 mos · Hydera

Developed a new feature for Qualcomm’s in-house debugging tool called as Regedit. Used in comparing two binary files of display registry and identify the differences. It has a selective
comparison option to compare specific register values and dynamically loads the data from XML file
for each processor. Qt software was used in creating this application.