Data Science Intern TASC Outsourcing

About the Role: We are seeking a Data Science Intern to join our Hyderabad team. In this role, you will assist in data collection, analysis, and model development under the guidance of senior data scientists. You will gain hands-on experience with real-world datasets, machine learning, and business intelligence tools, contributing to projects that drive data-driven decisions. Responsibilities: Collaborate with data scientists to collect, clean, and preprocess data from multiple sources Perform exploratory data analysis and identify patterns or anomalies Assist in developing, training, and validating machine learning and deep learning models Create interactive dashboards and visualizations using Power BI and Excel Write and optimize SQL queries to extract and manipulate data Document methodologies, workflows, and results Present findings and insights to team members and stakeholders Participate in team meetings and contribute to brainstorming sessions Required Qualifications: Pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or related field 0–1 year of experience in data science or analytics (including academic projects or internships) Proficiency in Python for data analysis (pandas, NumPy, scikit-learn) Basic understanding of machine learning and deep learning concepts Familiarity with SQL and ability to write queries Working knowledge of Excel for data manipulation and analysis Exposure to Power BI or other BI tools Strong analytical skills and attention to detail Good verbal and written communication skills Preferred Qualifications: Prior internship or project experience in data science or analytics Experience with deep learning frameworks such as TensorFlow or PyTorch Familiarity with cloud platforms (AWS, Azure, or GCP) Experience with data visualization libraries (Matplotlib, Seaborn) Knowledge of statistical modeling and hypothesis testing Version control experience (Git) Ability to present technical findings to non-technical audiences