We are looking for someone with experience with AWS Client and AI tooling, along with distributed computing tools such as DataBricks, Comprehend, and SageMaker; data visualization. Tools like QuickSight, Kibana and Splunk will give you extra comfort in this role to be successful.
Technical Skills and Requirements - Programming Skills: The data scientist demonstrates proficiency in programming languages such as Python or R. They write efficient and clean code to manipulate, analyze, and visualize data.
- Statistical Analysis: The data scientist possesses a strong foundation in statistics, understanding concepts like hypothesis testing, regression analysis, probability theory, and statistical modeling techniques.
- Machine Learning: The data scientist is familiar with machine learning algorithms and techniques, understanding supervised and unsupervised learning, feature engineering, model evaluation, and optimization.
- Data Manipulation and Cleaning: The data scientist has expertise in handling large datasets, cleaning data, and performing data preprocessing tasks. They use tools like pandas, NumPy, or dplyr to manipulate and transform data effectively.
- Data Visualization: The data scientist effectively communicates insights and findings through visual representations. They demonstrate proficiency in data visualization libraries and tools like Matplotlib, Seaborn, or Tableau.
- SQL and Databases: The data scientist understands structured query language (SQL) and works with databases proficiently. They extract, manipulate, and analyze data stored in relational databases efficiently.
- Big Data Technologies: The data scientist has knowledge of big data technologies like Apache Hadoop, Apache Spark, or distributed computing frameworks. They work with large-scale datasets and leverage distributed computing for data processing.