Data Scientist

Role Overview

Work with structured and unstructured datasets to discover meaningful patterns, develop predictive models, and generate data-driven insights that support business objectives and strategic decision-making.

What You Will Do

Collect, clean, process, and analyze large datasets from multiple sources to identify patterns, trends, and meaningful insights.

Why It Might Be a Fit

Ideal for an early-career professional who is passionate about statistics, programming, machine learning, and solving real-world problems through data.

Requirements

• Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence, Machine Learning, or a related technical field.
• 0–1 year of experience in Data Science, Machine Learning, Data Analytics, or a related technical role.
• Strong programming knowledge in Python and familiarity with data science libraries such as Pandas, NumPy, and Scikit-learn.
• Solid understanding of statistics, probability, linear algebra, and mathematical fundamentals.
• Familiarity with machine learning concepts, including supervised and unsupervised learning.
• Understanding of data preprocessing, data cleaning, feature engineering, and exploratory data analysis.
• Proficiency in SQL for querying, joining, filtering, and analyzing datasets.
• Familiarity with data visualization tools and libraries such as Matplotlib, Seaborn, or Plotly.
• Understanding of machine learning algorithms such as regression, decision trees, random forests, clustering, and classification.
• Familiarity with Jupyter Notebook, Google Colab, or similar development environments.
• Basic understanding of model evaluation, validation techniques, and performance metrics.
• Familiarity with Git and GitHub for version control and collaborative development.
• Strong analytical thinking, critical reasoning, and problem-solving abilities.
• Ability to interpret complex data and communicate findings clearly.
• Strong attention to detail, teamwork, and willingness to learn new technologies.