We are looking for a proactive Data Science, Data Analyst & Business Analyst Intern who can bridge the gap between data, technology, and business. The intern will work on GCP-based data pipelines, data analysis, machine learning, and business problem understanding, helping convert raw data into actionable business insights.
Key Responsibilities:
Business Analysis
Understand business requirements and translate them into data and analytics problems.
Work with stakeholders to define KPIs, metrics, and success criteria.
Analyze business processes and identify areas for data-driven optimization.
Prepare insight-driven summaries and recommendations for business teams.
Support use cases such as customer behavior analysis, operational efficiency, and forecasting.
Data Engineering & Pipelines
Assist in building and maintaining data pipelines on GCP.
Work with BigQuery, Cloud Storage, Cloud Functions / Dataflow.
Perform data ingestion from multiple sources (APIs, flat files, databases).
Monitor pipeline performance and data quality.
Data Cleaning & Preparation
Clean, preprocess, and validate raw datasets for analytics and ML use cases.
Handle missing values, anomalies, duplicates, and schema mismatches.
Conduct exploratory data analysis (EDA) to understand trends and patterns.
Data Analysis & Reporting
Write SQL queries to analyze large datasets.
Build dashboards and reports using powerbi or similar BI tools.
Generate insights, trends, and root-cause analysis for business questions.
Machine Learning & Modeling
Assist in developing and evaluating machine learning models.
Perform feature engineering and model validation.
Support ML use cases like prediction, segmentation, and anomaly detection.
Collaboration & Documentation
Collaborate with data engineers, product managers, and business teams.
Document business assumptions, data definitions, and analytical approaches.
Participate in sprint planning, reviews, and knowledge-sharing sessions.
Required Skills & Qualifications:
Pursuing or recently completed a degree in Data Science, Business Analytics, Computer Science, Statistics, Mathematics, or related fields.
Strong foundation in Python (pandas, numpy).
Working knowledge of SQL.
Understanding of data cleaning, EDA, and basic statistics.
Basic knowledge of machine learning concepts.
Ability to understand business problems and convert them into analytical tasks.
Exposure to Google Cloud Platform (GCP) is a plus.
Good to Have:
Experience with BigQuery, Cloud Storage, Dataflow.
Familiarity with ETL / ELT pipelines.
Knowledge of BI tools (Looker, Power BI, Tableau).
Exposure to Git and version control.
Strong communication and presentation skills.
What You’ll Gain:
Hands-on experience in business analysis + data analytics + ML.
Exposure to real-world GCP-based data systems.
Opportunity to work closely with business and product stakeholders.
End-to-end understanding of how data drives business decisions.
Mentorship and practical project experience.