Data Analyst / Data Scientist
Posted 522 days ago, which is unusual. The employer's own board was still carrying it when we last read it, just now.
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 522d ago
The date the source published, not the day we noticed it (2025-04-11). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
India
The description agrees: it names India.
What the ad says
…Location: Remote (India)…
Pay not stated
Similar roles pay A$1,675–2,250/mo
Middle 50% of 19 listings that do state pay — Operations · all levels · APAC · AUD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
workable employer's own board first seen 11d ago · last seen just now
The listing
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.