Top Companies Hiring Data Scientists in Bangalore
Top Companies Hiring Data Scientists in Bangalore - live data, real salary bands, top employers, and practical tips for job seekers in India. Updated regularl
See which of these jobs match your resume →Data Scientist market · Bangalore
Openings by city observed · reliable
Top employers hiring live · deduplicated
| Company | Open roles |
|---|---|
| Satsure | 5 |
| Sarvam AI | 5 |
| Navi | 5 |
| Lendingkart | 5 |
| Nielsen | 5 |
| Bosch Group | 5 |
| Ansrsource | 5 |
Salary Overview
Data Scientist compensation in India varies by city, company stage, and whether the role is product, platform, or growth-focused. Fixed pay is quoted in LPA (lakhs per annum); variable pay and ESOPs are common at startups. Always clarify fixed vs CTC before negotiating.
By Experience Level
| Level | Typical fixed (LPA) |
|---|---|
| Entry | 7-13 LPA |
| Mid | 16-26 LPA |
| Senior | 28-42 LPA |
| Lead+ | 38-55+ LPA |
Live index (Bangalore, n=4): P25 31 · median 50 · P75 62.5 LPA
By City
Bangalore / Hyderabad: Highest volume of tech roles; senior Data Scientist bands at top of range.
Mumbai / Delhi NCR: Strong fintech and consumer; premiums for leadership roles.
Pune / Chennai: GCC and enterprise SaaS; competitive base, lower equity upside.
Bangalore: Factor in cost of living vs Bangalore when comparing offers.
Negotiation Tips
- Anchor with data from 3+ offers or trusted peers at the same level.
- Negotiate fixed first; treat variable and ESOP separately.
- Ask for signing bonus if base is capped.
- Get the offer letter with break-up (basic, HRA, PF) before resigning.
- If competing offers exist, share timelines, not numbers, to accelerate decisions.
Total Comp Breakdown
CTC typically includes: Basic, HRA, special allowance, PF employer contribution, gratuity provision, and projected variable. Ask for in-hand estimate after tax. ESOPs at startups may not appear in CTC, model dilution and vesting cliff separately.
Market Snapshot
Bangalore leads India's Data Scientist hiring by a wide margin. As of 8 July 2026, knok jobradar counted 189 open Data Scientist roles in the city, more than Delhi (55), Hyderabad (38), Mumbai (22), Pune (19), and Chennai (10) combined. That gap reflects Bangalore's unique ecosystem: a deep talent pool, decades of R&D investment, and a startup culture unlike any other Indian city. The active employer list is a healthy mix of three distinct types, GCCs (global companies running large India teams), home-grown product companies, and well-funded startups. GCCs offer structured career ladders and international exposure. Product companies give you ownership over real user-facing systems. Startups move fast and give you breadth. Knowing which 'flavour' suits you before you apply makes every application sharper.
Top Employers
Here are the companies with the most open Data Scientist roles in Bangalore right now:
| Company | Open Roles | Category |
|---|---|---|
| Navi | 6 | Fintech startup |
| SatSure | 5 | Agri-tech startup |
| Sarvam | 5 | AI/LLM product startup |
| LendingKart | 5 | Fintech startup |
| Bosch Group | 5 | GCC, German engineering MNC |
| HackerRank | 4 | HR-tech product company |
| Warner Bros. Discovery | 4 | GCC, US media MNC |
| Oolka | 4 | Early-stage startup |
| Nielsen | 4 | GCC, data & analytics MNC |
| IDFC First Bank | 4 | Private sector bank |
What the mix tells you: - GCCs (Bosch, Warner Bros. Discovery, Nielsen): Stable scope, enterprise-scale data infrastructure, global visibility. Good if you want structure and a defined growth path.
- AI product companies (Sarvam, HackerRank): You sit close to the product. Sarvam is building India's own LLM stack, a rare chance to work on foundational models from Bangalore.
- Fintechs and startups (Navi, LendingKart, SatSure, Oolka): Cross-functional and fast-paced. Expect to own the full pipeline, model building, deployment, and stakeholder communication all in one role.
- Banking (IDFC First Bank): Risk modelling, credit scoring, and fraud detection in a regulated environment. Steadier pace, high-stakes use cases.
Salary Range
Salaries vary significantly by experience level. Here is what the market looks like for Data Scientists in Bangalore:
| Experience | Typical Range (LPA) |
|---|---|
| Entry level (0-2 years) | 8-16 |
| Mid level (3-5 years) | 18-30 |
| Senior (6-9 years) | 30-48 |
| Lead / Principal | 45-70+ |
GCCs like Bosch and Nielsen tend to pay toward the higher end of each band and often add bonuses and allowances. Startups like Navi and Sarvam typically mix competitive cash with equity, so the headline LPA may understate total value. For senior and principal roles, publicly reported figures on Glassdoor and levels.fyi show compensation at well-funded AI startups that can exceed the Lead/Principal band listed here. Always ask for a full CTC breakup at the offer stage.
How To Stand Out
With 189 active roles and a concentrated hiring market, getting noticed takes more than a tidy resume. Here is what actually works: 1. Show deployed work, not just notebooks. Interviewers at product companies and startups want to see models that went to production. A GitHub repo with a live ML API tells a better story than Kaggle medals alone.
2. Match your skills to the employer type. GCCs often want SQL, PySpark, and dashboarding alongside ML. Startups want Python, LLM fine-tuning, or MLOps. Tailor your resume language for each.
3. Learn the domain before you apply. Targeting SatSure? Know what geospatial and satellite data means for agriculture. Going for IDFC First Bank? Brush up on credit risk and RBI compliance basics.
4. Cloud certifications still help at entry level. AWS, GCP, or Azure ML certifications signal cloud readiness, which matters when companies run large training jobs on the cloud.
5. Write one sharp summary line. Recruiters skim hundreds of profiles. A line that states 'what you build and for whom' outperforms a generic objective statement every time.
Application Strategy
Here is a practical approach to landing a role at Bangalore's top Data Science employers: - Start with the active hirers above. The companies in the table are hiring right now. Apply while the window is open, active spurts close faster than most people expect.
- Use both company portals and job boards. Many roles appear on a company's careers page a day or two before they surface on LinkedIn or Naukri. Both channels catch different listings.
- Message HR or the hiring manager directly. A short, specific note on LinkedIn, mentioning one project or product of theirs you genuinely found interesting, lands far better than a blank connection request.
- Follow up after a reasonable gap. Recruiters at busy companies often revisit shortlists after a second touchpoint. One polite follow-up is not annoying, it signals genuine interest.
- Apply to several companies at once. Having multiple processes running in parallel gives you leverage and a fallback if one role moves slowly. If tracking new openings across dozens of companies starts feeling like a second job, knok checks 150+ job sites nightly, applies to jobs matching your resume, and messages HR for you, so you do not miss a window while you are busy at your current role.
Salary figures combine disclosed CTC from knok's indexed postings with level benchmarks for the India market. We quote fixed LPA unless noted; variable and ESOP are called out separately. Updated 2026-07-06. Not individual financial advice.
- knok job index, 166 matching roles (snapshot 2026-07-06)
- Satsure, 5 indexed openings
- Sarvam AI, 5 indexed openings
- Navi, 5 indexed openings
- Lendingkart, 5 indexed openings
- Nielsen, 5 indexed openings
- Indexed job postings with disclosed CTC
- Level benchmarks (IC vs lead) for India tech
Frequently asked
Which type of company is better for a fresher, a startup or a GCC?
It depends on what you want to learn first. GCCs like Bosch or Nielsen offer structured onboarding, defined roles, and exposure to large datasets, good if you want depth in a specific domain with mentorship in place. Startups like Navi or Sarvam throw you into real problems faster and broaden your skills quickly, but guidance may be thinner. If you are confident in your foundations and want speed, go startup. If you want process and mentorship as a base, a GCC is the safer first step.
Do I need a master's degree or PhD to get a Data Scientist role in Bangalore?
Not necessarily. Many companies in this list, especially fintechs and startups, hire strong candidates with a BTech and solid practical skills. A master's degree can help you clear the first screening round and may push your starting salary toward the upper end of the entry band. PhDs are mainly relevant for research-heavy roles at companies like Sarvam. For most roles here, a portfolio of real projects and strong fundamentals will matter more than the degree level.
What skills do most of these top companies look for?
Python is non-negotiable across all the companies in this list. SQL is equally important, even product companies expect you to pull and explore data independently. Machine learning fundamentals such as regression, classification, and tree-based models are table stakes. Beyond that, it varies by type: GCCs often want PySpark and cloud platforms; AI startups want LLM fine-tuning, RAG pipelines, or MLOps experience; fintechs want feature engineering and model monitoring at production scale.
How long does the hiring process usually take at these companies?
Startups like Navi or LendingKart move quickly and can wrap up from application to offer within a few weeks when they are in active hiring mode. GCCs like Bosch or Nielsen take longer due to multiple interview rounds and internal approval processes. Banking roles at IDFC First Bank can stretch further because of background checks and compliance sign-offs. Applying to several companies at once gives you leverage and means a slower process at one company does not leave you waiting with no options.
Is Bangalore still the best city in India for Data Scientist roles?
Based on current data, yes. Bangalore has 189 open Data Scientist roles compared to Delhi (55), Hyderabad (38), Mumbai (22), Pune (19), and Chennai (10), the gap is significant. The city's concentration of product companies, GCCs, and well-funded AI startups creates a depth of opportunity other cities have not yet matched. That said, Delhi and Hyderabad are growing and are worth watching if Bangalore's cost of living is a concern for you.
What is the difference between a 'Data Scientist' and a 'Data Analyst' role in these companies?
In most Bangalore companies, Data Analysts focus on reporting, dashboards, and answering business questions from existing data, the output is usually a chart or a recommendation. Data Scientists build predictive models and machine learning systems that automate decisions or surface patterns at scale, the output is usually code running in production. Some startups blur the boundary at entry level, so always read the job description carefully to check whether they expect you to build and deploy models or primarily analyse data.
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