- Apache Spark
- AWS
- Azure Data Factory
- Azure Databricks
- C++
- Docker
- Kubeflow
- Microsoft Azure Cloud
- MongoDB
- Python
- Problem-solving skills
- Data Science
- Deep Learning
- DevOps
- Machine learning
- MLOps
With over 7 years of experience as an Analytics Engineer and Data Scientist, I have a proven track record of delivering successful projects across a range of industries, including health, finance, telecommunications, and transportation. My ability to lead companies in the development of analytical and predictive systems is based on leveraging state-of-the-art ETL pipelines and utilizing the latest data engineering tools and best practices, resulting in an 80% time reduction in computation.
I possess excellent technical skills, including expertise in analytics, machine learning algorithms, statistical modeling, and database management. I am skilled in driving data-based decision-making, ensuring that clients receive the most innovative and cutting-edge solutions.
My skills and abilities include software development, artificial intelligence, data science, system design, and project management. I have worked with a range of tools and technologies, including Python, R, C++, NodeJS, TensorFlow, Pytorch, Sklearn, Huggingface, Ansible, Terraform, Airflow, Docker, Kubernetes, Ascend.io, Flask, Nginx, AWS SageMaker & Lambda, Tableau, Grafana, Looker, Pandas, Numpy, Ray, Spark, Kafka, Dramatiq, Celery, Postgres, Elasticsearch, MongoDB, Redis, Nebula, AWS timestream, HIVE, Parquet, HDFS, and AWS S3.