Job Description

About Us

Aeries Technology is a Nasdaq listed global professional services and consulting partner, headquartered in Mumbai, India, with centers in the USA, Mexico, Singapore, and Dubai. We provide mid-size technology companies with the right mix of deep vertical specialty, functional expertise, and the right systems & solutions to scale, optimize and transform their business operations with unique customized engagement models. Aeries is Great Place to Work certified by GPTW India, reflecting our commitment to fostering a positive and inclusive workplace culture for our employees. Read about us at https://aeriestechnology.com

About Business Unit

Corporate BU

Roles and Responsibility

Position/Title: Trainee - Data Science

Location: Hyderabad

Department: Dev/Engineering

Employment type: Trainee  

Experience: Fresher-2 years

Qualification: Graduate in Data Science, Computer Science, Statistics, or related fields

Shifts (if any): 11 am onwards (Candidate should be flexible to work as per business requirement)

Role & responsibilities:

• Assist in collecting, cleaning, and analyzing large data sets
• Support the development and testing of ML models and data-driven algorithms
• Generate insights through data visualization and basic statistical analysis
• Write clean, maintainable Python code for data-related tasks
• Collaborate with cross-functional teams to understand requirements and deliver results
• Document findings, code, and processes clearly for internal use

Key Skills & Tools:

• Proficiency in Python and key libraries (NumPy, Pandas, Scikit-learn, Matplotlib, etc.)
• Understanding of basic statistical concepts and machine learning algorithms
• Familiarity with SQL and data manipulation
• Exposure to BI tools (like Power BI or Tableau) is a plus
• Good problem-solving ability and eagerness to learn
• Strong communication and collaboration skills

Good to have:

• Certification or coursework in data science and machine learning
• Previous project work or internship experience in data science (preferred but not mandatory)