You will get Natural Language processing (NLP) Analytics and Model Building Expert
Project details
Advanced Natural language processing Analysis. I cover Bag of Words, Word Embeddings, Topic Modelling, Named Entity Recognition, Natural Language Generation, Text Mining, String Distance and Similarities, Fuzzy Matching, Sentiment Analysis, Text Summarization, etc. The models can be LDA, LSTM, Bagging, Boosting, etc. The tools can be Stanford NER, SpaCy, Scikit-Learn, TensorFlow, Gensim, etc
What's included
| Service Tiers |
Starter
$100
|
Standard
$200
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 6 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 6 | 6 | 6 |
Number of Scenarios | 2 | 3 | 4 |
Number of Graphs/Charts | 5 | 5 | 8 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
30 reviews
(26)
(2)
(2)
(0)
(0)
PM
Paul M.
Jun 23, 2022
He has done a great job. I have hired him five times for my projects. Excellent !
PM
Paul M.
Apr 12, 2022
He is committed to realising the works according to my particular requests. I have hired him several times because he knows what my projects were about. Thanks for all the works. Well done!
PM
Paul M.
Mar 24, 2022
He is committed to producing the god-quality works, and he knows what he is doing especially he is willing to customise my particular requests.
PM
Paul M.
Mar 12, 2022
He is agile, and is responsible. He has tried to achieve the goals of the project following my requests., He has tried to offer the extra miles. Thanks.
AA
Adnan A.
Aug 29, 2025
Need Data Engineer with expert level skills of Azure Delta Lake, Azure Data Bricks and Python
AP
Austin P.
Jun 18, 2024
Fix Spark Python Function
NA
Nasser A.
May 1, 2024
Data Management Fundamentals, Database Design and Implementation
NB
Nisha B.
Jan 30, 2024
SnapLogic: Need a Subject Matter Expert for reviewing MCQ Questions
AC
Ace C.
Nov 7, 2023
Guidance of a hadoop and hive sql statement
Very responsive, nice, and professional!
About Maad
Cloud Data & AI Engineer | GCP, AWS, Azure | AI Pipelines
100%
Job Success
Karachi, Pakistan - 4:28 am local time
With 7+ years of experience in data engineering and cloud architecture, I specialize in designing data-intensive systems that process large-scale data efficiently and turn it into actionable insights and intelligent automation.
🔹 What I Can Help You With
Cloud Data Engineering & Big Data Systems
End-to-end ETL/ELT pipelines on GCP, AWS, Azure & Databricks
BigQuery, Redshift, Synapse, Microsoft Fabric Lakehouse
Apache Spark / PySpark (Databricks, distributed processing)
GCP Dataflow, Pub/Sub, Cloud Functions, Composer (Airflow)
AWS Glue, Lambda, S3 | Azure Data Factory & Synapse
Batch & real-time streaming pipelines (Kafka, event-driven systems)
Data modeling (star schema, lakehouse & warehouse architecture)
GenAI & AI-Powered Data Applications
LLM integrations (ChatGPT, Claude, Gemini)
GenAI-based data pipelines & intelligent workflows
Natural Language → SQL / data querying systems
AI copilots, automation tools & internal assistants
Recommendation systems (e-commerce, product analytics)
Analytics & Data Products
Product analytics (GA4, user behavior, funnel analysis)
Marketing attribution & performance analytics
Business intelligence & reporting systems
Data-driven strategy & decision support solutions
🔹 What Makes Me Different
I don’t just build pipelines I design end-to-end data platforms that connect data engineering, big data processing, and GenAI into real business use cases.
My focus:
Scalable architectures (handling high-volume data workloads)
Cost optimization (BigQuery, Databricks, cloud-native systems)
Clean, reliable data models for analytics and AI
🔹 Tech Stack
GCP: BigQuery, Dataflow, Pub/Sub, Cloud Functions, Composer
AWS: S3, Glue, Redshift, Lambda
Azure & Fabric: Data Factory, Synapse, Fabric Lakehouse
Databricks & Big Data: Apache Spark, PySpark
Core: Python, SQL, Airflow, Kafka
GenAI: ChatGPT, Claude, Gemini
🔹 Typical Projects I Work On
Building scalable data pipelines (APIs, GA4, ERP → Data Warehouse/Lakehouse)
Designing cloud-native data platforms (GCP, AWS, Azure, Databricks, Fabric)
Developing GenAI-powered tools (chatbots, automation, data assistants)
Creating real-time and streaming data systems
Implementing recommendation engines and analytics platforms
If you're looking for someone who can design and build a scalable data platform or AI-driven solution tailored to your business, let’s connect.
Steps for completing your project
After purchasing the project, send requirements so Maad can start the project.
Delivery time starts when Maad receives requirements from you.
Maad works on your project following the steps below.
Revisions may occur after the delivery date.
Data Discovery
Understanding Problem and Data discovery
Data analysis
Exploratory data analysis and feature engineering steps