Data Analyst-Target

The iScale; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

The iScale in Bengaluru, India is seeking a data analytics professional to support merchandising decisions. You will perform data-driven analyses, build dashboards, and work with senior analysts to translate business questions into analytical solutions.

You will query large datasets using SQL and BigQuery, contribute to data pipelines, and apply predictive techniques under guidance. Strong communication and teamwork are essential in a fast-paced setting.

Qualifications

• Hands-on SQL with joins, volatile tables, and basic tuning.
• Experience with at least one BI visualization tool (PBI/Looker/Tableau).
• Knowledge of structured and unstructured data stores (Oracle, Hive, Hadoop).
• Exposure to large-scale datasets and data pipelines (BigQuery, Spark, Airflow).
• Familiarity with open-source languages like Python or R.
• Understanding analytic techniques (Regression, Time-series, Classification).
• Git and agile methodologies experience.
• Strong problem solving and communication skills.
• Interest in Retail/Merchandising/Marketing is a plus.
• Basic understanding of GenAI and LLM-based workflows.

Responsibilities

• Execute data analysis to support merchandising decisions using established frameworks.
• Assist scenario analysis by preparing data, running analyses, and summarizing results.
• Collaborate with senior analysts and stakeholders to define analytical needs.
• Develop reports, dashboards, and basic models to track performance.
• Apply predictive and diagnostic analytics under guidance.
• Query and analyze large datasets using SQL and platforms like BigQuery.
• Support data pipeline development with data engineering teams.
• Ensure accuracy and quality of outputs.
• Communicate findings through summaries and basic storytelling.
• Document analysis logic and assumptions for transparency.
• Follow data governance and responsible AI guidelines.

Skills

SQL proficiency

BI visualization

Big data concepts

Git & agile

Problem solving

Communication

Teamwork

GenAI awareness

AI tooling

analytical thinking

Education

B.Tech / B.E. or Masters in Statistics / Econometrics / Mathematics

Bachelors

Tools

SQL databases (Oracle, Hive)

GCP BigQuery

Spark

Airflow

HDFS

Python/R

Git

BI tools (Power BI/Tableau/Looker)

Job description

Key Responsibilities:

• Execute data analysis to support merchandising decisions using established frameworks and methodologies
• Assist with scenario and decision analysis by preparing data, running analyses, and summarizing results
• Work closely with senior analysts and stakeholders to understand business questions and analytical requirements
• Develop and maintain reports, dashboards, and basic models to track business performance and trends
• Apply foundational predictive and diagnostic analytics techniques under guidance
• Query and analyze large datasets using SQL and data platforms such as GCP BigQuery or similar tools
• Support data pipeline development and validation in partnership with data engineering teams
• Ensure accuracy, consistency, and quality of analytical outputs
• Clearly communicate findings through AI summaries and basic data storytelling
• Document analysis logic, definitions, and assumptions to support transparency and reuse
• Follow corporate data governance, privacy, and responsible AI guidelines

Requirements / About You:

Experience:Overall 2-6 years exp and relevant 1-3 years exp

Qualification:

TI : B.Tech / B.E. or Masters in Statistics /Econometrics/Mathematics equivalent

US : Bachelors

Skills required:

1. Hands on experience to Structured Query Language (SQL) syntax, including joins, volatile tables, and basic query tuning. And deep understanding of core DW/BI concepts.
2. Experience in at least 1 BI Visualization tool (i.e. PBI, Looker, Tableau) with ability to learn additional vendor and proprietary visualizations tools.
3. Working knowledge of structured (Oracle, Hive) and unstructured databases including Hadoop Distributed File System (HDFS)
4. Exposure to large-scale datasets using tools like GCP BigQuery, Spark, or SQL-based warehouses and data pipelines (using Airflow or similar tools)
5. Exposure to R, Python, Hive or other open-source languages/database
6. Understanding of analytical techniques (like Regression, Time-series models, Classification Techniques, etc.) to discover and measure key business drivers
7. Git source code management & experience working in an agile environment
8. Problem solving skills
9. Self-motivated and able to work in team settings in a fast-paced environment
10. Competent and curious to ask questions and learn to fill gaps
11. Good communication.
12. Experience with Retail, Merchandising, Marketing will be strong addons
13. Basic understanding of Generative AI (GenAI) and Large Language Model (LLM) based applications, including prompt engineering, RAG and AI-assisted workflows
14. Ability to leverage AI-powered tools to improve analytical productivity, automate