Schlagworte
Skills
IMPORTANT: FOR PROJECT INQUIRIES, PLEASE SEND THE PROJECT DESCRIPTION ONLY VIA EMAIL (pouyan@fard-ai.com), NO COLD CALLS PLEASE.
WICHTIG: BEI PROJEKTANFRAGEN BITTE DIE PROJEKTBESCHREIBUNG NUR PER E-MAIL (pouyan@fard-ai.com) SENDEN, BITTE KEINE KALTE ANRUFE.
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
WICHTIG: BEI PROJEKTANFRAGEN BITTE DIE PROJEKTBESCHREIBUNG NUR PER E-MAIL (pouyan@fard-ai.com) SENDEN, BITTE KEINE KALTE ANRUFE.
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
- Lead consultant in big data, AI, and cloud computing with an entrepreneurial mindset advising global corporations on data science, big data engineering, and solution architecture.
- Innovative data expert with 10+ years of project experience in architecture, implementation, and deployment of big data & analytics solutions in business environments resulting 10+ software platforms, 10 publications, and over 5 million dollars in company revenues.
- Highly detail-oriented data & AI solution architect leveraging domain knowledge, data analytics, effective communication, and data story-telling skills to generate actionable business insights across energy, aviation, automotive, life sciences & pharmaceutical, sales and marketing, and human resources industries.
Projekthistorie
07/2022
-
bis jetzt
Lead Data Scientist - NLP & Semantic Analytics
Global Pharmaceutical Company
(>10.000 Mitarbeiter)
Pharma und Medizintechnik
11/2021
-
06/2022
Solution Architect & MLOps Lead
Global Pharmaceutical & Biotech Company
(>10.000 Mitarbeiter)
Pharma und Medizintechnik
- End-to-end Deployment of ML models in the production environment using a self-developed MLOps framework
- Design & architecture of a cloud-based MLOps framework optimizing for automation of machine learning workflows, integration with enterprise data lakes, user-friendliness, and security
- Conducting requirements engineering and stakeholder management for the strategic planning of long-term IT initiatives
- Leading of a team of data scientists, data engineers, and DevOps engineers for the development of enterprise MLOps framework
- Technologies used: AWS Sagemaker, AWS Lambda, AWS Eventbridge, Python, Machine Learning, Apache Airflow, MLFlow
- Design & architecture of a cloud-based MLOps framework optimizing for automation of machine learning workflows, integration with enterprise data lakes, user-friendliness, and security
- Conducting requirements engineering and stakeholder management for the strategic planning of long-term IT initiatives
- Leading of a team of data scientists, data engineers, and DevOps engineers for the development of enterprise MLOps framework
- Technologies used: AWS Sagemaker, AWS Lambda, AWS Eventbridge, Python, Machine Learning, Apache Airflow, MLFlow
04/2021
-
03/2022
Lead Data Scientist & Data Engineer
Global Energy & Mobility Company
(>10.000 Mitarbeiter)
Energie, Wasser und Umwelt
- Leading the development of machine learning-based predictive maintenance use case based on IoT data on AWS cloud infrastructure
- End-to-end development & deployment of machine learning model using AWS Sagemaker
- Design of the reference cloud architecture for predictive analytics use cases in AWS
- Development & deployment of a streaming ETL pipeline for IoT sensor data used for data visualization and machine learning based on AWS infrastructure
- Conducting visual analytics activities on big data from maintenance & sales capabilities using Power BI, Plotly, and Python
- Technologies used: AWS Sagemaker, AWS Lambda, AWS Glue, AWS DynamoDB, AWS Athena, AWS S3, AWS RDS. AWS Cloud9, Python, Machine Learning, XGBoost, Plotly, Power BI, MLOps, MySQL, CI/CD
- End-to-end development & deployment of machine learning model using AWS Sagemaker
- Design of the reference cloud architecture for predictive analytics use cases in AWS
- Development & deployment of a streaming ETL pipeline for IoT sensor data used for data visualization and machine learning based on AWS infrastructure
- Conducting visual analytics activities on big data from maintenance & sales capabilities using Power BI, Plotly, and Python
- Technologies used: AWS Sagemaker, AWS Lambda, AWS Glue, AWS DynamoDB, AWS Athena, AWS S3, AWS RDS. AWS Cloud9, Python, Machine Learning, XGBoost, Plotly, Power BI, MLOps, MySQL, CI/CD
07/2021
-
12/2021
Senior Data Engineer
Global Chemical Company, United States
(>10.000 Mitarbeiter)
Sonstiges
- Development of big data pipelines on top of AWS infrastructure for high-dimensional data
- Technologies used: Python, Unit testing, Docker, Xarray, Dask, Bitbucket, CI/CD, AWS (EC2, S3, Parameter Store)
- Technologies used: Python, Unit testing, Docker, Xarray, Dask, Bitbucket, CI/CD, AWS (EC2, S3, Parameter Store)
05/2021
-
11/2021
Solution Architect & Lead Data Scientist
Global Transportation & Mobility Company, Germany
(5000-10.000 Mitarbeiter)
Transport und Logistik
- Design & architecture of data warehousing solutions in Azure Synapse
- Development & deployment of dynamic pricing solution in Azure cloud infra-structure
- Conducting data migration from on premise to Azure Synapse environment
- Technologies used: Azure Synapse, Azure Data Factory, Azure Blob, Azure Ku-bernetes Service, Azure Data Lake Storage, AzCopy, Python, Pyspark, Tableau, K-means Clustering, MLOps, CI/CD
- Development & deployment of dynamic pricing solution in Azure cloud infra-structure
- Conducting data migration from on premise to Azure Synapse environment
- Technologies used: Azure Synapse, Azure Data Factory, Azure Blob, Azure Ku-bernetes Service, Azure Data Lake Storage, AzCopy, Python, Pyspark, Tableau, K-means Clustering, MLOps, CI/CD
06/2020
-
04/2021
Lead Data Scientist & NLP Engineer
HR-tech startup
Internet und Informationstechnologie
- Development of proof-of-concept HR-tech solution for automated sourcing & screening of talents using NLP based on unstructured data.
- Technologies used: Python, Scala, SpaCy, NLTK, MongoDB, MariaDB, D3.JS, Javascript, MapReduce, Spark, Azure, Databricks, Snowflake, MLOps, CI/CD.
- Technologies used: Python, Scala, SpaCy, NLTK, MongoDB, MariaDB, D3.JS, Javascript, MapReduce, Spark, Azure, Databricks, Snowflake, MLOps, CI/CD.
09/2020
-
12/2020
Lead Big Data Strategy & Architecture Consultant
Global Biotech Company
(5000-10.000 Mitarbeiter)
Pharma und Medizintechnik
- Leading the data strategy & architecture initiative to conduct big data infrastructure health-checks and identifying the functional and process gaps in the client’s big data infrastructure.
- Requirement engineering and conducting stakeholder interviews multiple interviews and workshops with 25+ stakeholders across the organization.
- Conducting gap analysis and defining the long-term big data strategy roadmap.
- Definition and prioritization of actionable recommendations for the client’s digital transformation strategy including predictive analytics use cases.
- Requirement engineering and conducting stakeholder interviews multiple interviews and workshops with 25+ stakeholders across the organization.
- Conducting gap analysis and defining the long-term big data strategy roadmap.
- Definition and prioritization of actionable recommendations for the client’s digital transformation strategy including predictive analytics use cases.
10/2019
-
05/2020
Senior Data Scientist & NLP Engineer
Global Pharmaceutical Company
(>10.000 Mitarbeiter)
Pharma und Medizintechnik
Project: Advanced analytics dashboard for a semantic analytics use case
- Built advanced text analytics models (semi-supervised learning) based on complex & imbalanced datasets achieving 96% accuracy in the semantic inference of business insights.
- Designed and implemented an end-to-end big data analytics pipeline and deployed text analytics models in the client's existing big data infrastructure.
- Responsibilities involved requirements engineering, business analysis, stakeholder communication, communication between the technical team and product owner, the transition of requirements into user stories.
- Involved in managerial tasks such as big data architecture, user experience design, business analysis, and project management tasks.
- Technologies used: Python, Java, Apache Spark, HDFS, Docker, AWS, Azure, Google Cloud, RESTful API, Apache Solr, PostgreSQL, Dexi.io, Prodigy, Spacy, Tensorflow, PyTorch, D3.JS, Highcharts, Jenkins, PyCharm , Bitbucket, Jira, Confluence.
10/2019
-
10/2019
Senior Data Science & Solution Architecture Consultant
European Energy Company (via Sapient GmbH)
(500-1000 Mitarbeiter)
Energie, Wasser und Umwelt
Project: Design & architecture of algorithmic trading platform
- Activities included: Business analysis, Use case definition, Business development, Solution design with machine learning
07/2019
-
10/2019
Senior Data Scientist
Global automotive company (Via Sapient GmbH)
(>10.000 Mitarbeiter)
Automobil und Fahrzeugbau
Project: Advanced analytics dashboard for marketing mix modeling and demand forecasting
- Developed an advanced analytics dashboard for marketing mix modeling and demand forecasting for the global automotive company: developing an end-to-end visual analytics dashboard for demand forecasting, monitoring, and prediction of key KPIs in a performance marketing campaign using time series analysis.
- Technologies Used: Python, XGBoost, Azure, SQL, Dash, Jira, Confluence.
07/2019
-
09/2019
Senior Data Visualization & Analytics Specialist
Global automotive company (Via Sapient GmbH)
(>10.000 Mitarbeiter)
Automobil und Fahrzeugbau
Project: Development and maintenance of marketing analytics dashboard for a global automotive company
- Technologies used: Tableau, PowerBI, SQL
03/2019
-
04/2019
Business Analyst - AI & Data Science in Aviation
Global airline company (Via Accenture)
(>10.000 Mitarbeiter)
Transport und Logistik
Project: Business analysis for big data analytics use cases across aviation industry
- Activities included: Business analysis, Use case definition, Business development, Solution design with machine learning
02/2019
-
04/2019
Data Scientist - Financial Analytics
European Financial Institution (via Accenture)
(1000-5000 Mitarbeiter)
Banken und Finanzdienstleistungen
Project: Developing a finance dashboard for the visualization of historical trends along with forecasted trends of economic KPIs
- Technologies used: R Shiny, Machine Learning
01/2019
-
04/2019
Data Scientist & NLP Engineer
Global Information Technology Services Company (via Accenture)
(>10.000 Mitarbeiter)
Internet und Informationstechnologie
Project: Development of human resources analytics platform
- Developing analytics-driven capabilities for ranking of candidates in talent search engine based on natural language processing.
- Technologies used: Azure, Kubernetes, Python, ETL, SQL, Restful API, Flask, Machine Learning
09/2018
-
12/2018
Data Scientist
Global airline company (Via Accenture)
(>10.000 Mitarbeiter)
Transport und Logistik
Project: Merchandising intelligence for international airline company
- Developing an advanced analytics dashboard for driving customer analytics (pricing analytics) for the aviation client using big data, visual analytics, and machine learning technologies.
- Technologies used: Tableau, Python, R, Machine Learning, SQL, Hive
07/2018
-
08/2018
Business Analyst - Data Science & Machine Learning
European Railway Company (via Accenture)
(>10.000 Mitarbeiter)
Transport und Logistik
Project: Business analysis for analytics use cases across the transportation industry
- Activities included: Business analysis, use case definition, business development, solution design with machine learning
06/2018
-
07/2018
Business Analyst - Data Architecture
Global Pharmaceutical company (via Accenture)
(>10.000 Mitarbeiter)
Pharma und Medizintechnik
Project: Big data architecture planning for a global pharmaceutical company
- Activities include strategic planning, big data architecture, project management.
02/2015
-
04/2018
Machine Learning Scientist
TU Dresden
(1000-5000 Mitarbeiter)
Öffentlicher Dienst
Project: Predictive modeling of consumer behavior:
- Conducting two large-scale research studies concerned with predictive modeling of human decision making (consumer behavior) based on tracking the visual input.
- Activities involve machine learning algorithm development, exploratory data analysis, statistical modeling, data visualization, big data acquisition, and data preparation.
- Technologies used: Python, Scikit-learn, Matplotlib, seaborn, eye tracking, self-developed advanced machine learning algorithms, approximate inference, MATLAB.
- Resulted in 3 academic publications in renowned academic journals and conferences.
- Managed a team of 5 scientific staff for the acquisition of big data (~ 100,000 entries)
- from more than 120 participants in consumer behavior study.
- Strong presentation skills with expertise in training over 150 university students for programming, statistical thinking, data-driven approach.
11/2016
-
05/2017
Data Scientist & NLP Engineer
Why Apply
(< 10 Mitarbeiter)
Internet und Informationstechnologie
Project: Advanced analytics for an innovative recruitment platform
- Assisting the company to generate actionable insights for clients as well as developing an advanced analytics dashboard for extraction, integration, and visualization of data from internal and external sources.
- Used natural language processing and web analytics.
- Technologies used: Python, NLTK, pyQT, Google Analytics, Google Cloud Platform.
07/2016
-
09/2016
Data Engineer
The SaaS Co.
(10-50 Mitarbeiter)
Internet und Informationstechnologie
Project: Automated data pipelines for data-driven B2B sales and lead generation
- Developed an integrated data pipe-line for extracting, integrating, cleaning, and aggregating, and visualizing insights from a big data-set of 270 million entries
Technologies used: Python, Postgresql, IBM-Watson Cloud, Regex, NLP
11/2012
-
11/2014
Virtual Reality Technology Specialist & Data Analyst
University-clinic Tuebingen
(1000-5000 Mitarbeiter)
Pharma und Medizintechnik
Project: Virtual reality software for movement rehabilitation
- Virtual reality software for movement rehabilitation: developed a virtual reality software providing real-time feedback to users for specific hand movement exercises
using computer animation, machine learning, motion capture technologieslike: C ++, Ogre3D, Libsvm, MATLAB, data glove. - Data analysis and data acquisition for robotics and virtual reality projects: conductingdata acquisition and data preparation for large scale EU projects concerning
robotics using virtual reality and motion capture technologies like: Adobe Motion builder, Vicon Nexus, Ogre3D. - Software framework for real-time analysis of human physiological data: developing a software framework for real-time tracking and visualization of human physiological data using ECG. Technologies used: C ++, MATLAB, ECG, signal processing.
- Automated data pipeline for tracking and visualization of hand movements: virtual reality framework applied in movement rehabilitation. Technologies used: C ++, Ogre3d, TCP / IP.
03/2013
-
11/2013
Machine Learning Engineer
MPI Intelligent Systems
(>10.000 Mitarbeiter)
Internet und Informationstechnologie
Project: Developing software frameworks in machine learning and human-computer interaction in 2 research projects
- Technologies used: Python, Matlab, machine learning, optimization methods, control theory, neural networks
03/2012
-
12/2012
Business Development Consultant
Sooren systems Ltd.
(< 10 Mitarbeiter)
Internet und Informationstechnologie
- Driving business development activities like preparing RfP responses, closing international partnerships, client and partner negotiation, and content marketing.
- Closed 3 large-scale clients through RfP response process for developing enterprise portals
Reisebereitschaft
Verfügbar in den Ländern
Deutschland, Österreich und Schweiz
Remote: (Bevorzugt) bis zu 100% / (Preferred) Up to 100%
Vor-Ort: bis zu 10% / Onsite: Up to 10%
Technical Skills:
Vor-Ort: bis zu 10% / Onsite: Up to 10%
Technical Skills:
- Programming: Python, Java, Scala, R, C++, C#, Matlab
- Big Data: Spark, Hadoop, MapReduce, Kafka, Hive, Hue, Impala, Solr, Sqoop, Drill, Presto, Zeppelin
- Database: MySQL, PostgreSQL, SQL Server, T-SQL, MariaDB, Solr, MongoDB, Cassandra, Hbase
- Cloud:
- Azure: CLI, Data Lake/Blob Storage, Data Factory, Databricks, Polybase, Synapse Analytics, SQL DB, Cosmos DB, MLStudio, Cognitive Services, Data Studio, App Service, Container Service, Kubernetes Service, Azure Functions
- AWS: EMR, Athena, RDS, DynamoDB, Sagemaker, Comprehend, S3, Lambda, Quicksight
- Google Cloud: Natural Language, Vision
- Databricks
- DevOps: Docker, Jenkins, CI/CD
- Data Visualization: PowerBI, Tableau, R Shiny, Seaborn, Google Analytics
- Machine Learning: SKlearn, Tensorflow, Keras, pyTorch, DL4J, XGBoost, CNN, LSTM, BERT, ULMFit, Azure ML-studio, AWS Sagemaker
- Natural Language Processing: SpaCy, NLTK, SparkNLP, Gensim, CoreNLP, Textblob, Regex, AWS Comprehend, Prodigy
- Frontend: D3.JS, Plotly, Bubble, HighCharts, pyQt, Javascript, jQuery, CSS, HTML
- Web & Frameworks: Flask, Restful API, Swagger, JSON, Postman, TCP/IP
- Version control: Git, Github, Gitlab, Bitbucket
- Project management: Scrum, Confluence, Jira
- OS: Windows, Linux
- Editors: PyCharm, IntelliJ, VS Code, Atom, Eclipse
