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Data Analyst / Data Scientist

Role overview

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
  • 1–5 years of experience in a data analyst or data scientist role, preferably in a fast-paced or startup environment.
  • Strong proficiency in SQL and Python for data manipulation and analysis.
  • Experience building dashboards and visualizations using Tableau (or similar tools such as Power BI or Looker).

Responsibilities

  • Perform exploratory data analysis to identify trends, patterns, and opportunities within large datasets.
  • Build and maintain dashboards and reports using Tableau to visualize KPIs, performance metrics, and other analytical outputs.
  • Write efficient, well-structured SQL queries to extract, manipulate, and analyze data from various databases.
  • Use Python to develop scripts and workflows for data cleaning, transformation, and predictive modeling.

About the company

Weekday (YC W21) logo

Weekday (YC W21)

Staffing & Recruiting

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Company details

IndustryStaffing & Recruiting
Company size11 - 50

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Job description

This role is for one of the Weekday's clients
Salary range: Rs 300000 - Rs 1200000 (ie INR 3-12 LPA)


Min Experience: 1 years

Location: Remote (India)

JobType: full-time

We’re looking for a passionate and detail-oriented Data Analyst / Data Scientist to join our growing analytics team. This role is perfect for someone who thrives on solving complex problems using data, loves diving deep into datasets, and has a strong command of analytical tools and programming languages.

As a Data Analyst / Data Scientist, you will play a crucial role in helping teams make data-driven decisions by uncovering actionable insights from structured and unstructured data. You’ll work closely with stakeholders across departments—such as product, marketing, and operations—to understand their challenges and deliver meaningful analysis and visualizations that guide strategy and execution.

Requirements

Key Responsibilities:

  • Perform exploratory data analysis to identify trends, patterns, and opportunities within large datasets.
  • Build and maintain dashboards and reports using Tableau to visualize KPIs, performance metrics, and other analytical outputs.
  • Write efficient, well-structured SQL queries to extract, manipulate, and analyze data from various databases.
  • Use Python to develop scripts and workflows for data cleaning, transformation, and predictive modeling.
  • Collaborate with cross-functional teams to define data requirements and deliver insights to support business decisions.
  • Interpret data and communicate results clearly and effectively to both technical and non-technical stakeholders.
  • Participate in the development and improvement of data models, pipelines, and quality checks.
  • Stay up-to-date with industry trends, best practices, and new technologies in analytics and data science.

Requirements:

  • Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
  • 1–5 years of experience in a data analyst or data scientist role, preferably in a fast-paced or startup environment.
  • Strong proficiency in SQL and Python for data manipulation and analysis.
  • Experience building dashboards and visualizations using Tableau (or similar tools such as Power BI or Looker).
  • Solid understanding of statistical methods and ability to apply them to real-world business problems.
  • Strong analytical and problem-solving skills with attention to detail and accuracy.
  • Excellent communication and collaboration skills, with the ability to present findings in a clear and concise manner.

Nice to Have:

  • Exposure to machine learning techniques and libraries (e.g., scikit-learn, XGBoost, etc.).
  • Experience working with cloud-based data platforms (AWS, GCP, or Azure).
  • Familiarity with version control tools like Git and workflow automation tools like Airflow.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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