Jr Data Scientist

Responsibilities

• Collect, clean, preprocess, and analyze structured and unstructured datasets.
• Develop and implement machine learning models to solve business problems.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and insights.
• Build predictive models and evaluate their performance using appropriate statistical techniques.
• Develop data visualizations and dashboards to communicate findings effectively.
• Collaborate with data engineers, software developers, business analysts, and stakeholders to deliver data-driven solutions.
• Optimize machine learning models for scalability, accuracy, and performance.
• Follow software development best practices, including version control and Agile methodologies.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Information Technology, Software Engineering, Computer Engineering, Mathematics, Statistics, Artificial Intelligence, or a related technical field.
• 1–4 years of professional experience in data science, software development, analytics, machine learning, or a related technical role.
• Strong programming skills in Python, R, SQL, Java, or similar programming languages.
• Understanding of statistics, probability, linear algebra, and machine learning fundamentals.
• Familiarity with data analysis libraries such as Pandas, NumPy, Scikit-learn, or similar tools.
• Knowledge of SQL, relational databases, and data modeling concepts.
• Exposure to cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP) is a plus.
• Knowledge of machine learning frameworks such as TensorFlow, PyTorch, Keras, or XGBoost is preferred but not required.
• Strong analytical, problem-solving, and communication skills.
• Willingness to relocate to Atlanta, GA for the paid training program and travel or relocate as required for client engagements across the United States.

Preferred Qualifications

• Internship, academic, or personal projects involving data science, machine learning, artificial intelligence, or predictive analytics.
• Experience with data visualization tools such as Tableau, Power BI, or Matplotlib.
• Knowledge of Git or other version control systems.
• Familiarity with Jupyter Notebook, Google Colab, or similar development environments.
• Understanding of Agile/Scrum development methodologies.