DATA ANALYST

Company: Newton School

Location: Bangalore (On-site)

Experience: Fresher / 0–1 Year

ABOUT THE ROLE:

Newton School is looking for a Data Analyst with strong analytical thinking and a solid foundation in SQL, Python, data visualization, and business problem-solving.

The role involves working with business, product, operations, finance, and engineering teams to analyze data, understand business problems, identify meaningful insights, and support data-driven decision-making.

You will work with datasets from different sources, write SQL queries, perform analysis using Python, build dashboards and reports, track key business metrics, and help identify trends, anomalies, and opportunities for improvement.

This role is ideal for someone who has strong fundamentals, enjoys solving problems using data, and wants to build a career in analytics by working on real-world business problems.

KEY RESPONSIBILITIES

Data Analysis & Business Problem Solving

• Analyze business data to identify trends, patterns, anomalies, and opportunities.

• Understand business questions and translate them into structured analytical problems.

• Perform exploratory and diagnostic analysis to understand business performance and key drivers.

• Support root-cause analysis for business and operational problems.

• Develop structured analyses to support business decisions and performance improvement.

• Work with business and product stakeholders to understand requirements and provide relevant data and insights.

• Identify opportunities where data, reporting, or automation can improve existing processes.

SQL & Data

• Write SQL queries using joins, subqueries, CTEs, aggregations, and other data manipulation techniques.

• Extract, clean, transform, validate, and analyze data from different sources.

• Work with structured datasets across databases and analytical systems.

• Perform data validation and reconciliation to ensure accuracy and consistency.

• Understand basic database structures, tables, relationships, and data flows.

• Identify data quality issues and collaborate with relevant teams to resolve them.

Python & Automation

• Use Python for data analysis, data manipulation, exploratory analysis, and basic automation.

• Work with commonly used Python libraries such as Pandas, NumPy, and Matplotlib.

• Write scripts to clean, transform, and analyze datasets.

• Automate repetitive analytical or reporting tasks where appropriate.

• Apply Python to solve practical business and data problems.

Business Intelligence & Visualization

• Build and maintain dashboards and reports to track business performance and key KPIs.

• Use visualization tools such as Power BI, Tableau, or Looker to present data effectively.

• Understand business metrics, KPIs, and reporting requirements.

• Create clear visualizations that help stakeholders understand trends and performance.

• Communicate analytical findings in a simple, structured, and actionable manner.

Stakeholder & Cross-functional Collaboration

• Collaborate with Product, Engineering, Operations, Finance, and Business teams on analytical requirements.

• Understand the business context behind analytical requests rather than focusing only on data extraction.

• Translate data and analytical findings into clear business insights.

• Communicate findings effectively to both technical and non-technical stakeholders.

• Work with engineering and data teams to understand data sources and resolve data-related issues.

• Track the impact of analysis and recommendations where applicable.

REQUIRED SKILLS

• Strong foundation in SQL, including joins, subqueries, aggregations, CTEs, and data manipulation.

• Good understanding of Python for data analysis and manipulation.

• Strong analytical and problem-solving skills.

• Ability to approach business problems in a structured and logical manner.

• Understanding of basic statistics and quantitative analysis.

• Understanding of business metrics, KPIs, and data-driven decision-making.

• Ability to clean, validate, analyze, and interpret datasets.

• Understanding of data visualization and dashboarding.

• Ability to communicate analytical findings clearly.

• Strong attention to detail and willingness to learn.

PREFERRED QUALIFICATIONS

• Hands-on experience with BI tools such as Power BI, Tableau, or Looker.

• Familiarity with Python libraries such as Pandas, NumPy, and Matplotlib.

• Understanding of databases, data models, ETL/ELT concepts, and data pipelines.

• Familiarity with Excel or Google Sheets for data analysis.

• Understanding of statistical analysis, experimentation, forecasting, or analytical modeling.

• Exposure to product analytics, business intelligence, operations analytics, or similar analytical areas.

• Familiarity with APIs, cloud data platforms, or modern data tools is a plus.

• Relevant internships, academic projects, personal projects, hackathons, or case studies demonstrating practical data analysis skills are preferred.

• Bachelor's degree in Engineering, Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.

IDEAL CANDIDATE

We are looking for someone who:

• Has strong fundamentals in SQL and is comfortable working with data.

• Can use Python to clean, analyze, and explore datasets.

• Enjoys solving business problems using data rather than simply creating reports.

• Is curious about understanding why a metric changed, not just what changed.

• Can take a business question and work through the data to arrive at a logical conclusion.

• Has strong numerical reasoning and attention to detail.

• Can communicate analytical findings clearly and concisely.

• Is comfortable learning new tools, datasets, and business domains quickly.

• Demonstrates analytical ability through internships, projects, coursework, competitions, or independent work.

• Enjoys working with both business and technical teams to solve real-world problems.

EXPERIENCE

Freshers and candidates with up to 1 year of relevant experience in data analytics, business analytics, product analytics, business intelligence, or a similar analytical role are eligible to apply.

Candidates with strong SQL and Python fundamentals and demonstrated analytical ability through internships, academic projects, personal projects, hackathons, case studies, or other practical work are encouraged to apply.

Prior full-time professional experience is not required.