Data Scientist

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Job description

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.

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