Meisam Ghafarlangroudi-Machine Learning Engineer
Check rate
Experience
Machine Learning Engineer
Geeks
- Utilized a Large Language Model (LLM) at WordUp, tailored to enhance vocabulary learning by understanding and generating contextual examples, improving personalized learning experiences
- Developed a high-performance Fast API service for retrieving high-K similar vectors with batch querying capabilities. This service is crucial for enabling efficient Retrieval Augmented Generation (RAG) and semantic search applications
- Designed and implemented a high-performance Python ETL pipeline, optimizing CPU and I/O utilization and streamlining data cleansing logic, resulting in a 30% reduction in processing time
- Utilized machine learning to analyze user behavior and predict churn, identifying key engagement trends that led to a 15% increase in user retention and satisfaction
- Developed a Customer Lifetime Value (CLTV) prediction model, leading to a 10% increase in average CLTV through targeted retention efforts
Machine Learning Engineer
Mellat Bank
- Developed a sentiment analysis model using BERT to analyse Instagram comments, achieving over 85% accuracy and providing actionable insights for customer engagement strategies
- Developed a news trading algorithm using Fin-BERT and GPT-3 and sentiment analysis to predict short-term price movements in stock and Forex markets, achieving a 20% improvement in trading signal accuracy
- Developed machine learning models to predict cryptocurrency price movements using historical price data and news sentiment analysis
- Built an ensemble model combining XGBoost with a deep autoencoder to detect anomalies in credit card transactions in real time, reducing false positives by 25% and improving fraud recall by 15%
- Implemented a customer churn prediction model, reducing churn by 15% and enhancing customer retention strategies
- Built recommendation engines to suggest banking products to customers, enhancing cross-selling opportunities by 22%
- Engineered a forecasting model using DeepAR to predict credit usage with an R-square value exceeding 80%, optimizing financial planning
Data Scientist
Hosh and Dansh
- Created machine learning models to predict inventory needs, reducing holding costs by 15%
- Built models to predict customer churn, enabling proactive retention efforts that decreased churn rate by 12%
- Designed a personalized recommendation system that increased average basket size by 8%
- Implemented algorithms that adjusted pricing based on demand forecasting, increasing revenue by 10%
Industry experience
See where this freelancer has spent most of their professional time.
Experienced in Banking and Finance, Education, Information Technology, and Retail.
Business area experience
See which departments and functions this freelancer has contributed to most.
Experienced in Business Intelligence, Information Technology, Investments and M&A, Marketing, and Supply Chain Management.
Skills
Programming
- Python
- R Programming
- Scala
Database Systems
- Snowflake
- Ms Sql Server
- Nosql
- Milvus
- Mongodb
- Bigquery
- Elasticsearch
- Postgre
- Chroma
Cloud
- Aws (S3, Glue, Redshift, Lambda, Kinesis)
- Google Cloud Platform (Gcp)
- Azure
ETL
- Airflow
- Dbt
- Ssis
- Ssas
Software Development
- Apis Services
- Docker
- Terraform
- Kubernetes
- Ci/Cd
- Fastapi
- Git
- Github
- Slack
- Jira
- Confluence
- Kubeflow
- Agile Development
Reporting Tools
- Ms Power Bi
- Google Looker
- Tableau
- Metabase
- Google Analytics
- Data Studio
Big Data & Parallel Processing
- Apache Spark
- Ray
- Hadoop
Machine Learning & Predictive Analytics
- Regression Models
- Classification
- Time Series Analysis
- Deep Learning (Tensorflow, Pytorch)
- Llm
- Faiss
- Scann
- Huggingface
- Rag
- Bert
- Sentiment Analysis
- Nlp
- Vector Search
- Web Scraping
- Mmm
- Llama
- Lora
- Llama Index
- Langchain
- Transformers
- Pymc
- Pgvector
- Pytest
Languages
Education
Science and Culture University, Iran
Master of Financial Engineering and Risk Management · Financial Engineering and Risk Management · Tehran, Iran, Islamic Republic of
IU International University of Applied Sciences, Berlin
Master of Data Science · Data Science · Berlin, Germany
Azad University, Iran
Bachelor of Industrial Engineering · Industrial Engineering · Tehran, Iran, Islamic Republic of
Statistics
Experience
Global experience
Expertise
Qualifications
Profile
Frequently asked questions
Have questions? Find more information here.
Meisam is based in Berlin, Germany.
Meisam speaks the following languages: English (Advanced), German (Intermediate).
Meisam has at least 7 years of experience. During this time, Meisam has worked in at least 2 different roles and for 3 different companies. The average length of individual experience is 3 years and 6 months. Note that Meisam may not have shared all experience and actually has more experience.
Based on recent experience, Meisam would be well-suited for roles such as: Machine Learning Engineer, Data Scientist.
Meisam's most recent position is Machine Learning Engineer at Geeks.
In recent years, Meisam has worked for Geeks and Mellat Bank.
Meisam is most experienced in industries like Banking and Finance, Education, and Information Technology. Meisam also has some experience in Retail.
Meisam is most experienced in business areas like Business Intelligence, Information Technology, and Investments and M&A. Meisam also has some experience in Marketing and Supply Chain Management.
Meisam has recently worked in industries like Banking and Finance, Education, and Information Technology.
Meisam has recently worked in business areas like Business Intelligence, Information Technology, and Investments and M&A.
Meisam holds a Master in Financial Engineering and Risk Management from Science and Culture University, Iran, a Master in Data Science from IU International University of Applied Sciences, Berlin and a Bachelor in Industrial Engineering from Azad University, Iran.
The availability of Meisam needs to be confirmed.
Daily rate distribution
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Average rates for similar positions
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 26 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
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