
Data Scientist
4 days ago
Required Skills:
- Programming Languages: Strong proficiency in Python, with experience in SQL.
- Machine Learning: Hands-on experience with Scikit-learn, TensorFlow, Keras, PyTorch, or similar ML libraries.
- Data Analysis: Strong skills in Pandas, NumPy, and Matplotlib for data manipulation and analysis.
- Statistical Analysis: Experience applying statistical methods to data, including hypothesis testing and regression analysis.
- Cloud Platforms: Familiarity with AWS, Azure, or Google Cloud for deploying models and using cloud-native data services (e.g., AWS Sagemaker, Azure ML).
- Data Visualization: Experience using Tableau, Power BI, Matplotlib, Seaborn, or Plotly for creating visualizations.
- SQL & Databases: Proficiency in SQL for querying relational databases and working with NoSQL databases (e.g., MongoDB, BigQuery).
- Version Control: Experience using Git for version control.
Desirable Skills:
- Big Data Technologies: Familiarity with tools like Apache Hadoop, Spark, Dask, or Google BigQuery for processing large datasets.
- Deep Learning: Experience with deep learning frameworks such as TensorFlow, PyTorch, or MXNet.
- NLP & Computer Vision: Experience with natural language processing (NLP) using spaCy, NLTK, or transformers, and computer vision using OpenCV or TensorFlow.
- MLOps: Familiarity with MLOps tools like Kubeflow, MLflow, or DVC for managing model workflows.
- Data Engineering: Experience with ETL tools like Apache Airflow, Talend, AWS Glue, or Google Dataflow for data pipeline automation.
Tools & Technologies:
- Machine Learning: Scikit-learn, TensorFlow, PyTorch, Keras, XGBoost.
- Data Analysis: Pandas, NumPy, Matplotlib, Seaborn, Plotly.
- Cloud Platforms: AWS, Google Cloud, Azure.
- Databases: MySQL, PostgreSQL, MongoDB, BigQuery, Snowflake.
- Data Visualization: Tableau, Power BI, Matplotlib, Seaborn, Plotly.
- Version Control: Git.
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