Brolly Academy | Data Science

Data Science Jobs in Hyderabad

Salary, Skills, Freshers & Career Guide 2026

If you are searching for data science jobs in Hyderabad, the city offers opportunities across data science and machine learning, artificial intelligence, analytics, business intelligence and data engineering. Hyderabad’s technology ecosystem includes IT, healthcare, pharmaceuticals, finance, consulting, retail and other industries.

This guide covers data science jobs in Hyderabad for freshers and experienced professionals, required skills, salary, job roles, job portals, resume tips, interview preparation and a practical career roadmap.

Nani
September 11, 2026
11:07 am

Data Science Jobs in Hyderabad — Complete Guide at a Glance

Yes. Hyderabad has active opportunities for data science and related roles. Do not search only for the exact title “Data Scientist”; related titles can provide additional entry points.

Job Role

Main Work

Key Skills

Best Entry Point For

Data Scientist

Predictive modelling and insights

Python, SQL, ML, Statistics

Candidates with strong ML and projects

Data Analyst

Analysis and reporting

SQL, Excel, Power BI

Freshers building analytics skills

ML Engineer

Build and deploy ML models

Python, ML, APIs, Cloud

Production-focused ML careers

AI/ML Engineer

Build AI/ML applications

Python, ML, Deep Learning

AI/ML-focused candidates

BI Developer

Dashboards and reporting

SQL, Power BI, Tableau

Business reporting

Data Engineer

Data pipelines and infrastructure

SQL, Python, ETL, Cloud

Data infrastructure careers

Associate Data Scientist

Analytics and modelling

Python, SQL, Statistics

Freshers and early-career candidates

Fresher Opportunities

Freshers can enter data science through internships, associate, analyst and junior roles. Current fresher-oriented listings may ask for Python, SQL, Statistics, NumPy, Pandas, Scikit-learn and data-processing knowledge.

Core Skills to Learn

To prepare for Data Science Jobs in Hyderabad, focus on the core data science skills. The table shows what to learn and the practical outcome you should achieve.

Core Skill

What to Learn

What You Should Be Able to Do

Python

Functions, data structures, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn

Load, clean, analyze and visualize data; build a basic ML model

SQL

SELECT, filtering, JOINs, GROUP BY, CASE, subqueries, CTEs, window functions, aggregations

Retrieve, transform and analyze data from databases

Statistics

Probability, distributions, variance, correlation, hypothesis testing, regression, A/B testing

Understand data patterns and support data-driven decisions

Pandas & NumPy

DataFrames, arrays, data manipulation, filtering and transformations

Clean, transform and analyze datasets efficiently

Data Cleaning

Missing values, duplicates, inconsistent data and data preprocessing

Prepare reliable datasets for analysis and machine learning

Data Visualization

Power BI, Tableau, Matplotlib and Seaborn

Present trends, patterns and insights clearly

Machine Learning

Regression, classification, decision trees, random forests, boosting, clustering, feature engineering, cross-validation and model evaluation

Select appropriate algorithms, train models and evaluate their performance

Git & GitHub

Version control, repositories, commits and project documentation

Maintain and showcase data science projects professionally

Communication

Explaining analysis, presenting findings and communicating business impact

Explain technical results in a clear, understandable way

Practical Projects

Real-world datasets, EDA, feature engineering, ML models and business interpretation

Demonstrate practical skills through 2–3 meaningful projects

Deep Learning

Neural networks and deep learning fundamentals

Strengthen your profile for AI-focused roles

NLP

Natural language processing concepts and applications

Work with text and language-based data

LLMs & Generative AI

Modern language models and AI-generation techniques

Create and understand intelligent, AI-powered solutions

MLOps

Model deployment and production-focused ML practices

Understand how ML models are moved toward production

Cloud

Cloud concepts relevant to data and ML workloads

Strengthen your profile for production-focused data and AI roles

Key Takeaway

Start with Python, SQL, Statistics, Data Analysis and Machine Learning, then build your profile with visualization, Git/GitHub and practical projects. For AI-focused careers, add Deep Learning, NLP, LLMs & Generative AI, MLOps and Cloud based on your target role.

Salary in Hyderabad

Salary depends on experience, company, specialization and technical depth. Current Indeed data lists an average annual salary of about ₹12.62 lakh for Data Scientist roles in Hyderabad. Treat this as a market indicator rather than a guaranteed offer.

Where to Find Jobs

Use multiple sources instead of relying on one job portal:

Naukri: Naukri
LinkedIn Jobs: LinkedIn Jobs
Indeed: Indeed
Internshala: Internshala
Instahyre: Instahyre
Cutshort: Cutshort
Shine: Shine

Fresher Job Strategy, Portfolio, Resume, Interviews & 90-Day Roadmap

Freshers can get data science jobs without extensive professional experience when their portfolio demonstrates practical ability. Build 2–3 meaningful projects rather than many copied tutorials.

Career Stage

Main Focus

Expected Outcome

Days 1–30

Python, SQL, Statistics

Strong fundamentals and regular practice

Days 31–60

ML, EDA, Visualization, Projects

2–3 practical projects

Days 61–75

Resume, LinkedIn, GitHub

Job-ready professional profiles

Days 76–90

Applications, Networking, Interviews

Consistent job search and interview practice

Build Practical Projects

Choose realistic problems instead of copying tutorials. Useful examples include churn prediction, forecasting, fraud detection, recommendation and NLP projects.

A good project should show:

A clear business problem
Dataset and data source
Data cleaning
Exploratory analysis
Feature engineering
Model building
Model evaluation
Business interpretation
Clear GitHub documentation

For example, a churn project should explain which customers may leave, why they may leave and what action the company could take.

Build an ATS-Friendly Resume

Keep the resume simple, one page where possible, and tailored to the target role. Highlight relevant skills and measurable project outcomes.

Instead of:

“Created a machine-learning project.”

Use:

“Developed a customer churn prediction model in Python using Scikit-learn and compared multiple classification algorithms.”

Replace vague statements with evidence. For example:

“Worked with data” → “Cleaned and analyzed customer data using Pandas and SQL to identify churn patterns.”

“Made dashboards” → “Built an interactive Power BI dashboard communicate key business metrics.”

Optimize LinkedIn

Use a clear headline such as:

Data Science Expertise | Python | SQL | Machine Learning | Statistics

Add relevant skills, projects and portfolio links.

Apply to Related Roles

Do not search only for “Data Scientist.” Also search for:

Associate Data Scientist
Junior Data Scientist
Data Analyst
ML Engineer
AI/ML Engineer
Analytics Associate
Research Associate
Data Science Intern

Related roles can provide additional entry points and useful experience for a future data science transition.

Interview Preparation

Prepare for three major areas:
Technical: Python, SQL, Statistics, Machine Learning, Pandas and scikit-learn model evaluation.
Case studies: Translate a business problem into a data problem before choosing an algorithm.
Project questions: Be ready to explain algorithm choice, missing data, evaluation metrics, overfitting, trade-offs and results.
A strong candidate should explain business impact, not only technical terminology.

Common Mistakes to Avoid

Applying without reading the job description
Listing skills you cannot demonstrate
Copying projects you cannot explain
Using the same resume for every job
Preparing only theory
Applying only for Data Scientist titles
Having no portfolio evidence
Ignoring communication skills

Which Data Role Should You Target?

If You Enjoy…

Consider…

Prioritize…

Dashboards and business reports

Data Analyst / BI Developer

SQL, Excel, Power BI/Tableau

Building prediction models

Data Scientist

Python, Statistics, ML, SQL

Deploying ML systems

ML Engineer

Python, ML, APIs, Cloud

Building AI applications

AI/ML Engineer

Python, ML, Deep Learning, GenAI

Building data pipelines

Data Engineer

SQL, Python, ETL, Cloud

Starting with limited experience

Data Analyst / Associate Data Scientist / Intern

Python, SQL, Statistics, Projects

Quick Action Plan

Choose 2–3 target job titles.
Compare their job descriptions and identify repeated skills.
Strengthen Python, SQL and Statistics fundamentals.
Build 2–3 practical projects aligned with those roles.
Document the projects clearly on GitHub.
Create an ATS-friendly resume tailored to each role.
Optimize your LinkedIn profile.
Set job alerts using multiple job titles.
Apply consistently while networking with relevant professionals.
Prepare for Python, SQL, ML, project and business-case interviews.
Track feedback and improve weak areas.

Why This Guide Is More Useful Than a Job-Listing Page

Most job-board pages primarily display vacancies. This guide also helps users understand Hyderabad’s market, related job titles, skills, salary, fresher strategy, portfolio projects, ATS resume optimization, interview preparation, common mistakes and a 90-day roadmap.

The goal is to help a reader move from learning to employment, not simply collect data science certificates.

FAQ’s

1. Are there data science jobs in Hyderabad?

Yes. Hyderabad has opportunities across data science, analytics, AI and machine learning.

2. Can freshers get data science jobs in Hyderabad?

Yes. Freshers can target internships, associate, analyst and junior roles.

3. What skills are required?

Python, SQL, Statistics, Machine Learning and Data Visualization are core skills.

4. Is Python mandatory?

Python is one of the most commonly requested programming languages.

5. Is SQL important?

Yes. SQL is essential for retrieving and analyzing data.

6. What is the Data Scientist salary in Hyderabad?

Current Indeed data reports approximately ₹12.62 lakh annually as a Data Scientist average.

7. What is a fresher's salary?

It varies by company, role, skills and experience.

8. Can I get a job without a data science degree?

Yes. Relevant technical skills and practical projects can help candidates from different backgrounds. See the data science course eligibility guide for a broader overview.

9. Can B.Tech students apply?

Yes. B.Tech graduates can apply for relevant data and AI/ML roles.

10. Can B.Sc students apply?

Yes. Mathematics, Statistics and computer-related backgrounds can be useful.

11. Is an MSc required?

No. It is useful for some specialized positions but is not universally required.

12. Which companies hire data scientists?

Companies across technology, healthcare, finance, consulting and other sectors hire data professionals.

13. Which websites are best for jobs?

Naukri, LinkedIn, Indeed, Internshala, Instahyre and Cutshort are useful.

14. Are internships available?

Yes. Current listings include data-science internships and fresher-oriented positions.

15. Can I get a job without experience?

Yes, particularly through projects, internships and entry-level roles.

16. How many projects should I build?

Two or three strong projects are better than many copied projects.

17. Which projects are good?

Churn prediction, forecasting, fraud detection, recommendation and NLP projects are useful examples.

18. Is machine learning necessary?

It is important for many Data Scientist roles, while analyst roles may emphasize SQL and reporting.

19. Is Power BI useful?

Yes. It is particularly useful for analytics and BI roles.

20. Is Tableau required?

No. It is useful but not mandatory for every data role.

21. Do data scientists need cloud skills?

Cloud knowledge is increasingly useful, especially for production-focused roles.

22. Is Generative AI useful?

Yes. GenAI knowledge can strengthen profiles for modern AI-focused roles.

23. Do I need GitHub?

It is not mandatory, but GitHub can demonstrate practical project skills.

24. How can I improve my resume?

Highlight relevant skills, measurable project outcomes and practical experience.

25. What is asked in interviews?

Expect Python, SQL, Statistics, ML, projects and business-case questions.

26. How long does it take to become job-ready?

It depends on your background, learning pace and practical experience.

27. Can non-CS students enter data science?

Yes. Quantitative backgrounds such as Mathematics, Statistics and Engineering can be useful.

28. Should freshers apply for Data Analyst jobs?

Yes. Analytics roles can provide valuable experience for a future data science transition.

29. How can I find new jobs?

Use job alerts, multiple job titles and company career pages.

30. What is the best way to get a data science job?

Build strong skills, create practical projects, optimize your resume, apply strategically and prepare for interviews.

Conclusion

Data science offers multiple career paths in Hyderabad, from Data Analyst and BI Developer roles to Data Scientist, ML Engineer, AI/ML Engineer, and Data Engineer positions. Choosing the right path depends on your skills, interests, and long-term career goals rather than simply focusing on the highest-paying role.

For freshers, building a strong foundation in Python, SQL, statistics, data visualization, and machine learning is an important first step. However, learning these skills becomes more valuable when combined with practical projects, real-world problem-solving, resume preparation, GitHub development, and interview practice.

At Brolly Academy, we focus on helping learners turn these skills into practical, job-ready capabilities through hands-on training, real-world projects, structured learning, certification guidance, and 100% Placement Assistance. Whether you are a fresher starting from the basics or looking to transition into a data science career, our goal is to provide the guidance and practical exposure needed to move confidently toward your career objectives.

If you are planning to build your data science career in Hyderabad, choosing the right learning path and getting consistent hands-on experience can make a meaningful difference. Brolly Academy is here to support you from learning the fundamentals to becoming job-ready and pursuing the right career opportunities in data science.