Akash Joshi

About Akash Joshi

Accomplished data scientist with 8+ years of experience leveraging advanced machine learning models, predictive analytics, and data storytelling to drive business growth and customer satisfaction. Proven track record of spearheading data-driven strategies that resulted in business and product growth. Thrives in fast-paced environments, driving measurable outcomes through innovative data products and strategic decision-making.Core Competancies - Machine Learning & Predictive Analytics, MLOps, LLM & Generative AI applications, Data Engineering, End-to-End Data Pipeline Development, Data Visualization & Storytelling, Cloud & Big Data Ecosystems, Statistical Analysis & A/B Testing, Cross-Functional Collaboration & LeadershipTechnical Skills:• Programming Languages: SAS, R, Python, SQL, C, C++, XML, HTML, JavaScript• Tools: VS Code, Spyder, Jupyter, AirFlow, Dbt, Tableau, R Studio, Splunk, Stitch, Segment, Salesforce, Power BI, Informatica, MATLAB, SQL Server, Qlik Sense, DBeaver, ActiveBatch, Workato• Databases: Google BigQuery, Snowflake, MySQL, Oracle, IBM DB2• Big Data Technologies: Splunk, Hadoop, Hive, Sqoop, Pig, Impala, Flume, Santry, kafka• Analysis Techniques: Data Processing, various Supervised and Unsupervised learning algorithms for classification, regression, clustering and association analysis tasks, Conjoint Analysis, Recommendation Model, PCA, Factor Analysis• Version control & automation: git, SVN, ActiveBatch, AirFlow• Misc: Data Mining, Statistical Analysis, Statistical Inference, Data Visualization, MS PowerPointee

Experience

1. Principal Ai Software Architect

   IBM

   Aug 2025 — Present · New York, NY, US

   Architect, build, and operate agentic AI systems using IBM open-core technologies, including OpenRAG, OpenSearch, ContextForge, and AgentOps, with a focus on real-world production workloads- Implement end-to-end GenAI and RAG pipelines, covering document ingestion, chunking, embeddings (e.g, NVIDIA, Docling), vector indexing, reranking, and inference using IBM- and Azure-hosted LLMs- Tune and optimize latency, throughput, cost, and answer quality by owning prompt engineering, runtime orchestration, grounding strategies, caching, model selection, and retrieval/evaluation loops- Design and run offline and online evaluation frameworks, define quality and business KPIs, instrument telemetry and observability, and continuously improve systems using user feedback and production signals.

Education

• The University of Texas at Dallas

  Master’s Degree, Business Analytics

  2016 — 2018

• Gujarat Technological University (GTU)

  Bachelor of Engineering (B.E.), Electronics and Communications Engineering

  2009 — 2013

• Shree Vidyanagar School

  Schooling, Science Stream

  2003 — 2009

Skills

• Python
• Data Modeling
• Oracle Database
• Hadoop
• C++ Language
• Manual Testing
• Data Management
• C++
• Data Analysis
• Tableau
• Xml
• Informatica
• Sql
• Linux
• Databases
• Business Analytics
• Data Mining
• Regression Testing
• R
• Microcontrollers
• 8051 Microcontroller
• Statistical Data Analysis
• Hp Quality Center
• Dbvisualizer
• Core Java
• Matlab
• C
• Machine Learning
• Requirements Gathering
• Programming Languages
• Data Warehousing
• Mysql
• Microsoft Sql Server
• Statistics
• Business Intelligence
• Intel 8085
• Software Development Life Cycle (Sdlc)
• Embedded Systems
• Data Science
• Analytics