Data Scientist

Required Skills & Experience • Python or similar tools, used for: o Data Manipulation and Analysis for handling and cleaning large datasets, performing mathematical operations, and exploring data distributions. o Visualization, including line charts, scatter plots, histograms, and heatmaps, to uncover patterns and trends. o Machine Learning Algorithms for tasks such as classification, regression, clustering, and dimensionality reduction. • SQL, used for: o Data Retrieval: SQL is used to extract specific data from databases based on predefined criteria, enabling analysts to answer questions and gain insights. o Data Manipulation: SQL can be used to update, insert, or delete data within databases, ensuring data accuracy and consistency. o Database Management: SQL is essential for creating, managing, and optimizing database structures, ensuring efficient data storage and retrieval. • Tableau or Power BI or similar tools, used for: o Data Visualization: These tools enable the creation of interactive dashboards and reports that present data in a visually appealing and understandable manner. o Data Storytelling: By combining data visualization with narrative elements, these tools help communicate insights effectively to stakeholders. o Data Exploration: Users can explore data interactively, drilling down into details or zooming out to see the big picture. Nice to Have Skills & Experience • Machine Learning Frameworks, used for: o Model Development: TensorFlow and PyTorch provide the necessary tools and infrastructure for building and training machine learning models, including deep neural networks. o Deployment: These frameworks can be used to deploy models into production environments, allowing them to make predictions on new data. o Experimentation: Machine learning frameworks support experimentation with different algorithms, hyperparameters, and architectures to optimize model performance. • Jupyter Notebook or similar tools, used for o Data Exploration: Jupyter Notebook provides a flexible environment for combining code, text, and visualizations, making it ideal for exploring data and experimenting with different approaches. o Reproducibility: Notebooks can be shared and executed by others, ensuring reproducibility of results and facilitating collaboration. o Education and Training: Jupyter Notebooks are commonly used for teaching and learning data science concepts, as they allow for interactive experimentation and exploration. Job Description The Associate Data Scientist identifies business trends and problems through complex data analysis and interprets results from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining. Designs, develops, and implements the most valuable business solutions for the organization, prepares data for ingestion and consumption, implements data models, develops databases to support business solutions, gains exposure to complex tasks within the job function, reports to a manager, works under close management on projects/matters of limited complexity in a support role.