نبذة عني
Experience in entire data science life cycle, i.e. Sourcerce =>clean=>explore=>communicate • Experience in Data analysis, Data preparation, Data manipulations, Data Exploration & Visualization using • Pandas and NumPy, M…
Experience in entire data science life cycle, i.e. Sourcerce =>clean=>explore=>communicate • Experience in Data analysis, Data preparation, Data manipulations, Data Exploration & Visualization using • Pandas and NumPy, Matplotlib, Seaborn, Statistics, Algebra and Tableau, ARIMA, FMCG,CLV• Experience in Natural Language Processing, Text
Preprocessing, and Feature Engineering on text data• Text Classification, relationship extraction, sentiment Analysis, topic segmentation • Define the vision and strategy for AI/ML products and features • Gather and prioritize requirements from stakeholders and customers• Coordinate the development team and ensure timely delivery of AI projects• Conduct market research and competitive analysis to identify opportunities for AI integration • Exposure to Deep learning using Tensor Flow • Experience in Continuous build deployment and Integration through Django.
الخبرة
AI Engineer
• Build a Formulated procedures for data extraction, transformation and integration of health care data •Develop and implement ML algorithms and models• Design and create data pipelines for data preprocessing and feature engineering• Fine-tune and optimize ML models for performance and scalability• Collaborate with data scientists and software engineers to deploy ML solutions into production• Continuously monitor and improve the performance of ML models• Exp on seamless integration of deployed models with data sources, data pipelines, and data storage in Azure• Deploy models as web services or APIs using Azure Kubernetes Service (AKS) or Azure Container Instances (ACI)• Strong understanding of cloud computing concepts, Azure services, and resource management• Proficiency in scripting and automation using PowerShell, Azure CLI, or other relevant tools.• Performed Exploratory data analysis to draw meaningful insights from the data. • Generic OCR: NLP, NER Hugging face
transformer.
AI Engineer
• Build a Formulated procedures for data extraction, transformation and integration of health care data •Develop and implement ML algorithms and models• Design and create data pipelines for data preprocessing and feature engineering• Fine-tune and optimize ML models for performance and scalability• Collaborate with data scientists and software engineers to deploy ML solutions into production• Continuously monitor and improve the performance of ML models• Exp on seamless integration of deployed models with data sources, data pipelines, and data storage in Azure• Deploy models as web services or APIs using Azure Kubernetes Service (AKS) or Azure Container Instances (ACI)• Strong understanding of cloud computing concepts, Azure services, and resource management• Proficiency in scripting and automation using PowerShell, Azure CLI, or other relevant tools.• Performed Exploratory data analysis to draw meaningful insights from the data. • Generic OCR: NLP, NER Hugging face
transformer.
AI Engineer
• Build a Formulated procedures for data extraction, transformation and integration of health care data •Develop and implement ML algorithms and models• Design and create data pipelines for data preprocessing and feature engineering• Fine-tune and optimize ML models for performance and scalability• Collaborate with data scientists and software engineers to deploy ML solutions into production• Continuously monitor and improve the performance of ML models• Exp on seamless integration of deployed models with data sources, data pipelines, and data storage in Azure• Deploy models as web services or APIs using Azure Kubernetes Service (AKS) or Azure Container Instances (ACI)• Strong understanding of cloud computing concepts, Azure services, and resource management• Proficiency in scripting and automation using PowerShell, Azure CLI, or other relevant tools.• Performed Exploratory data analysis to draw meaningful insights from the data. • Generic OCR: NLP, NER Hugging face
transformer.
Data scientist
To understand the business use cases from clients and convert them into a well-defined problem statement and explain it to the development team.
To identify data sets required to develop predictive models for solving internal and external business problems.
To fill data gap by gathering data, designing annotation portal, and conducting data annotation by human annotators.
To explore data sets and identify data transformation and data quality needs for targeted applications.
To develop algorithms and predictive models to derive insights and business value from data.
To provide leadership and mentorship to other members of the team.
Identify and implement use cases which might help the organization business development.
To interpret results and produce actionable business insights that lead to measurable business and consumer experience performance improvements.
To Operationalize, publish, and monitor successful models to shape business and data science strategy.
To partner with other departments to solve problems and identify trends and opportunities.
To define and develop the program for metrics creation, data reporting collection, modeling, and the operational performance.
To work cross-functionally to define problem statements, collect data, build analytical models, and make recommendations.
To routinely communicate metrics, progresses and other key indicators to leadership.
To lead and support various ad hoc projects, as needed, in support of Organizations’ Business strategy.
Data Scientist
AI Engineer|Data Scientist|Data Analyst|DB|ML DL Python Hadoop HDFS NLP R
Artificial Intelligence Engineer, Data Scientist, Generative AI Engineer, Business Analytics, Machine Learning, Deep Learning, Data Analyst, Data Engineer II NLP, Python Developer, Computer Vision, Power BI
To understand the business use cases from clients and convert them into a well-defined problem statement and explain it to the development team.
To identify data sets required to develop predictive models for solving internal and external business problems.
To fill data gap by gathering data, designing annotation portal, and conducting data annotation by human annotators.
To explore data sets and identify data transformation and data quality needs for targeted applications.
To develop algorithms and predictive models to derive insights and business value from data.
To provide leadership and mentorship to other members of the team. Identify and implement use cases which might help the organization business development.
To interpret results and produce actionable business insights that lead to measurable business and consumer experience performance improvements.
To Operationalize, publish, and monitor successful models to shape business and data science strategy.
To partner with other departments to solve problems and identify trends and opportunities.
To define and develop the program for metrics creation, data the operational reporting collection, modeling, and performance.
To work cross-functionally to define problem statements, and make analytical models, collect data, build recommendations.
To routinely communicate metrics, progresses and other key indicators to leadership. To lead and support various ad hoc projects, as needed, in support of Organizations’ Business strategy.