Siri Kademani — Business Development Executive

Data Alchemist | AI/ML Enthusiast | Analytics Professional Embracing the mantra "Learn and be curious always," I continuously explore emerging technologies and methodologies, turning each challenge into an opportunity for growth and innovation. Whether it's experimenting with new algorithms, diving into the latest ML frameworks, or exploring novel data visualization techniques, my appetite for learning remains insatiable. Transforming raw data into actionable insights at Amazon. With 6+ years in Data Science and Business intelligence, coupled with a Master's in Business Analytics, I'm on a mission to push the boundaries of AI and machine learning. My toolkit includes: • ETL wizardry • Statistical sorcery • SQL mastery • Python prowess • BI tool expertise Skilled in ETL, data science, statistics, SQL, Python, and leading BI tools like Tableau and data platforms like Snowflake, I've successfully led initiatives in automating processes, developing actionable dashboards, and optimizing decision models. Passionate about developing cutting-edge solutions in NLP, computer vision, and advanced analytics. Always seeking to collaborate with industry pioneers to craft innovative algorithms and ethical AI applications. Currently in seek of mentors who can help me pave my career path in AI research science and data science. Aiming to Build AI Models.

Stackforce AI infers this person is a Data Engineer and Analyst specializing in SaaS and E-commerce industries.

Location: Seattle, Washington, United States

Experience: 5 yrs 7 mos

Skills

Business Intelligence
Data Engineering
Ai Development
Data Science
Data Analytics

Career Highlights

Led AI hackathon developing chatbot for real-time metrics.
Transformed raw data into actionable insights at Amazon.
Skilled in advanced analytics and machine learning.

Work Experience

Amazon

Business Intelligence Engineer II | Accounting (1 mo)

BIE Data Science | Selling Partner Experience (11 mos)

Technical Business Analyst | Seller trust Analytics (7 mos)

Gainwell Technologies

Data Engineer (4 mos)

W. P. Carey School of Business – Arizona State University

Statistical Analyst (3 mos)

Axon

Data Scientist (9 mos)

kipi.bi

Business Intelligence Engineer (8 mos)

Career Break

Professional development (9 mos)

Accenture in India

Data Engineer (7 mos)

Accenture

Associate Data Engineer (1 yr 9 mos)

Education

Master of Science at Arizona State University

Bachelor of Engineering at KLE Technological University - Hubballi (India)

Siri Kademani

Business Development Executive

Seattle, Washington, United States5 yrs 7 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Led AI hackathon developing chatbot for real-time metrics.
Transformed raw data into actionable insights at Amazon.
Skilled in advanced analytics and machine learning.

Stackforce AI infers this person is a Data Engineer and Analyst specializing in SaaS and E-commerce industries.

Contact

Skills

Core Skills

Business IntelligenceData EngineeringAi DevelopmentData ScienceData Analytics

Other Skills

Python (Programming Language)Amazon AthenaAWS GluePandas (Software)SQLAmazon QuickSightExtract, Transform, Load (ETL)CradleAmazon DynamoDBAmazon S3AWS LambdaStatisticsA/B TestingCausal InferenceAmazon Bedrock

About

Experience

Amazon

3 roles

Business Intelligence Engineer II | Accounting

Feb 2026 – Present · 1 mo

Python (Programming Language)Amazon AthenaAWS GluePandas (Software)SQLAmazon QuickSight+2

BIE Data Science | Selling Partner Experience

Promoted

Feb 2025 – Jan 2026 · 11 mos

Data Engineering and analytics on Seller Central/Vendor Central Applications/Subscription channels.
Spearhead data engineering and analytics initiatives for Seller Central/Vendor Central applications, developing robust ETL pipelines that increased data processing efficiency by 30%
Design and implement self-service analytics solutions, empowering stakeholders to access actionable insights independently, reducing ad-hoc request turnaround time by 65%
Led AI hackathon by developing chatbot using Amazon Bedrock and RAG concept during organizational hackathon, enabling Product Managers to access real-time metrics through natural language queries, reducing reporting overhead by 75%.
Develop and maintain scalable data pipelines utilizing AWS tech stack (Redshift, DynamoDB, Andes), transforming raw data into meaningful insights
Drive continuous improvement in data accessibility and quality through automation and process optimization, resulting in a 40% reduction in data discrepancies
Led end-to-end SP DSI estimation project for Seller Mobile App adoption, engineering ANDES datasets and ETL processes across US/EU5/JP marketplaces; drove data science collaboration to quantify app impact, resulting in identification of 90% GMS lift ($21K) for 3.1K established sellers and 81% lift ($20K) for 4.3K new sellers, enabling data-driven decisions for app promotion strategy and seller engagement initiatives.
Led seller satisfaction initiative for Prime Day 2025's 'Wrap' feature, implementing analytics model to identify and celebrate 500K successful sellers across US/IN marketplaces through personalized milestone recognitions and performance celebrations; enhanced seller experience by showcasing year-over-year growth achievements.
Technical Skills:
Tools : AWS (Redshift, DynamoDB, Andes, S3), Amazon Bedrock, Claude,QuickSight
Data Engineering: ETL, Python, SQL, Data Pipeline Development
Analytics: Business Intelligence, Predictive Modeling, Statistical Analysis

Extract, Transform, Load (ETL)CradleAmazon QuickSightAmazon DynamoDBAmazon S3AWS Lambda+5

Technical Business Analyst | Seller trust Analytics

Jul 2024 – Feb 2025 · 7 mos

1. Collaborated with product and tech to track Seller engagement with DYK launch via reporting for all Sellers in scope of GPSR, providing stakeholders with valuable insights into seller engagement and potential SX improvements. Through deep-dive analysis of low post-launch engagement, the team identified a critical issue stemming from upstream 'home pod region' changes that prevented the DYK widget from displaying to 50% of sellers (981K), demonstrating the value of data-driven problem-solving in feature rollouts.
2. Saved 50% downtime by building pro-active alarms for the existing data pipelines to avoid any failure/false reporting.
3. Worked cross-functionally to create and integrate an alternative W8-BEN [an tax compliance initiative WW] reporting solution into the existing de-risking dashboard, enabling centralized tracking of Seller Journeys for AEF-onboarded initiatives (except DAC7) and demonstrating agility in addressing urgent business needs.
4. Dialed Up 30K sellers for DAC7 [an EU Tax compliance initiative] and analysed the strategic seller impact on de-risking, In scope sellers to AEF that consisted of Account health dashboard (AHD) and Account Health Rating (AHR).

Amazon RedshiftSQLData PipelinesExtract, Transform, Load (ETL)A/B TestingData Analytics+1

Gainwell technologies

Data Engineer

Feb 2024 – Jun 2024 · 4 mos · Kansas, United States · Remote

1. Maintaining and enhancing data pipelines using Data stage.
2. Executing test cases in ALM for the Medicaid provider and manager websites led to a significant 20% improvement in website functionality and reliability.
3. By identifying and addressing potential issues proactively, I not only enhanced user experience but lso bolstered confidence in the websites' performance, ultimately driving greater satisfaction and efficiency for users.

Extract, Transform, Load (ETL)DataStageHP Application Lifecycle ManagementData Engineering

W. p. carey school of business – arizona state university

Statistical Analyst

Oct 2023 – Jan 2024 · 3 mos · Tempe, Arizona, United States · Remote

SCM 519: Analytical Decision Modeling II
Converting Excel decision and optimization models and simulations into Python scripts using Python libraries such as NumPy and pandas.

Decision ModelingPython (Programming Language)Data Analytics

Axon

Data Scientist

Jan 2023 – Oct 2023 · 9 mos · Scottsdale, Arizona, United States · Hybrid

1. Devised a robust binary classification model for text categorization, utilizing Natural Language Processing (NLP) techniques.
2. Successfully automated the time-consuming task of manually categorizing customer reviews, resulting in a remarkable time savings equivalent to approximately 16 hours of arduous manual work. This automation freed up valuable resources for more strategic initiatives.
3. Led the development of Tableau dashboards to present KPIs such as Avg. Promotors, Detractors, and Neutrals Net Promoter Score (NPS), contributing to a 25% reduction in time spent on manual data compilation and report generation. This enhanced data accessibility and facilitated quicker and data-driven decision-making.

Data ValidationVisualizationData AnalyticsDatabasesNatural Language Processing (NLP)Reporting & Analysis+16

Kipi.bi

Business Intelligence Engineer

Oct 2021 – Jun 2022 · 8 mos · Bangalore · Hybrid

Responsibilities:
1. Discover the sales, orders and transaction data along with social media data and performed data modelling by coming with facts and dimensions tables and in turn building the schemas . Snowflake schema was built for this model.
2. Data manipulation, data cleaning using Python
3. Prepared wire frames of tableau dashboards using Blasmiq.
4. Prepared tableau dashboards based on the business requirements with back end snowflake integration.

Data ValidationVisualizationData AnalyticsDatabasesReporting & AnalysisExtract, Transform, Load (ETL)+16

Career break

Professional development

Jan 2021 – Oct 2021 · 9 mos

Took time off to :
1. Upskill: Online course completion
a. Learn Machine Learning & Data Mining in Python - https://www.udemy.com/certificate/UC-4358b6b7-da12-4b13-a856-a36d10ae565d/
b. Beginners Guide to AI (Artificial Intelligence) - https://www.udemy.com/certificate/UC-a693b063-f4a6-4584-93a9-37eaac939592/
c. Certificate in Qlik Sense Analytics Development- https://www.udemy.com/certificate/UC-cb48278c-7e57-4d34-8b35-08b7205a36b3/
2. Study and give competitive exams for higher studies.
3. Pursued side hustles : digital marketing

Accenture in india

Data Engineer

May 2020 – Dec 2020 · 7 mos · Bengaluru, Karnataka, India

‘FMR Data Ontology’ - Responsibilities
1. Discovered the raw financial data by collaborating with SMEs and analysed the gaps and discovered insights which were further served as inputs for the AI use case models.
2. Performed Data cataloging using Alation and presented the entire analysis and insights to the chapter group of the company.
3. Worked on maintaining and enhancing processes by sourcing the data from SQL developer to Qlik sense using cronjobs.
4. Agile methodology helped me with better project management and leadership skills, also used JIRA board for the same.
5. Also automated two manual jobs :
A. A monthly job using a crontab schedule. Automated the process end to end using Unix shell scripts the queries for logic were written in SQL.
B. A weekly job that automatically sends two reports via email every week at a particular time.
Initially, these jobs were taking a manual effort of a day or two. After automation, the manual effort is reduced to almost nil.

Data ValidationVisualizationSQLData AnalyticsDatabasesUnix+20

Accenture

Associate Data Engineer

Aug 2018 – May 2020 · 1 yr 9 mos · Bengaluru Area, India

Training in Big Data Stream (09/2018 – 10/2018)
Was able to explore the big data stream which comprised of HadoopEco systems such as HDFS, Kafka, Cassandra, Hive, Scala.
Costco Project (12/2018 – 06/2019)
1. Executed end-to-end ETL UAT testing & monitored GCP Composer scheduling, promptly resolving any errors or bugs encountered, resulting in a 20% reduction in testing and debugging time. This streamlined process ensured the timely deployment of ETL pipelines, saving approximately 8 hours per week.
2. Employed Google Cloud Shell for efficient data import and export from Google Cloud Storage, leading to a 15% reduction in data transfer time compared to traditional methods. This optimization resulted in an estimated time saving of 5 hours per week.
3. Headed maintenance of the weekly scheduling process, ensuring smooth operations and settling any issues to guarantee error-free report generation. This proactive approach minimized disruptions and potential errors, contributing to a 98% reduction in report generation errors and saving an estimated 10 hours per month in troubleshooting and corrective actions.
FMR India (07/2018 – 12/2020)
Performed the DATA ONTOLOGY task basically to dig in the present data from the different data sources and apply business logic using SQL (used SQL developer tool mostly) in order to derive the business insights.