PlaySimple Games Data Science Intern Hiring Overview
PlaySimple Games, a mobile gaming company, is hiring a Data Science Intern in Bangalore for an in-office role. The internship is focused on real data science and machine learning problems, with work that includes Python, Apache Spark, Machine Learning, and Deep Learning. Exposure to LLM/GenAI is a plus, and Kaggle or GitHub projects are valued. The role is suitable for a Master's degree candidate, and there are 2 openings. The stipend is Rs.40,000/month, the duration is 6 months, and the application deadline is 3 September 2026 via Internshala.
PlaySimple Games is offering 2 openings for a Data Science Intern role in Bangalore, with a stipend of Rs.40,000/month for 6 months.
Role Focus and Work Environment
This internship is designed for candidates who want direct exposure to practical data science work rather than a purely theoretical assignment. The opportunity is centered on solving real data science and ML problems, which suggests that the work is expected to be applied and hands-on. The company is hiring for an in-office position in Bangalore, so the role is not remote. For candidates who want to build experience in a structured workplace setting, the location and format are clearly defined.
The company behind the role is PlaySimple Games, identified as a mobile gaming company. That context matters because the internship sits inside a product-driven environment where data science and machine learning are likely to be used in practical ways. While no further project details are provided, the description makes it clear that the intern will be working on real problems rather than simulated exercises. This makes the role especially relevant for candidates looking to strengthen applied skills.
The internship also stands out because it combines several technical areas in one position. The listed tools and domains include Python, Apache Spark, Machine Learning, and Deep Learning. In addition, LLM/GenAI exposure is mentioned as a plus, which signals interest in candidates who have explored newer AI-related areas. The overall focus is broad enough to appeal to applicants with different but related technical strengths.
What the role emphasizes
- Real data science and ML problems
- Work using Python
- Work using Apache Spark
- Exposure to Machine Learning and Deep Learning
- LLM/GenAI exposure as a plus
The role description does not mention any additional responsibilities beyond these areas, so it is best understood through the skills and problem types explicitly listed. That makes the internship straightforward to interpret: it is a technical data science position with a practical, applied focus. Candidates who already have project experience in related areas may find the role especially aligned with their background. The mention of project work also suggests that demonstrated ability matters alongside formal education.
Skills and Technical Areas Mentioned
The internship highlights a set of technical skills that define the kind of work the intern is expected to support. Python is included, which is a core language for data science and machine learning tasks. Apache Spark is also listed, indicating that the role may involve working with larger-scale data processing or distributed computing workflows. Alongside these, the internship includes Machine Learning and Deep Learning, showing that the position spans both foundational and advanced AI-related work.
The mention of LLM/GenAI exposure as a plus is important because it shows openness to candidates who have explored newer AI tools or approaches. Since it is described as a plus rather than a requirement, it should be understood as an advantage rather than a mandatory qualification. This gives applicants a chance to present relevant exposure if they have it, while still keeping the core expectations centered on the listed data science and ML stack. The role therefore balances established technical skills with interest in emerging areas.
Another notable point is the value placed on Kaggle and GitHub projects. That means practical evidence of work matters, not just classroom learning or degree status. Candidates who have built and shared projects may be able to show their ability to apply concepts in a visible way. Since the content specifically says these projects are valued, they should be treated as a meaningful part of the application profile.
Technical profile highlighted in the listing
- Python for data science work
- Apache Spark for data processing-related work
- Machine Learning for model-focused tasks
- Deep Learning for advanced AI-related tasks
- LLM/GenAI exposure as an added advantage
- Kaggle and GitHub projects as valued proof of work
The combination of these skills suggests a role that is both technical and portfolio-friendly. Applicants who have worked on notebooks, repositories, or competition-style projects may find that their experience fits the stated preferences well. At the same time, the listing does not say that every skill is mandatory, so the safest reading is that the internship welcomes candidates with relevant exposure across these areas. The emphasis is on capability, practical work, and readiness to contribute.
Eligibility, Preference, and Application Fit
The internship says that a Master's degree candidate is preferred. This is the only educational preference mentioned, so it should be treated as the clearest academic signal in the listing. The content does not provide any additional degree requirements, branch requirements, or experience thresholds. As a result, the most accurate interpretation is that the company is looking for candidates whose academic background aligns with advanced study and technical work.
Because the role values Kaggle and GitHub projects, applicants with a visible project history may have an advantage. These projects can help demonstrate practical understanding of Python, Machine Learning, Deep Learning, or related data science work. The listing does not specify how projects will be evaluated, but the fact that they are explicitly valued makes them relevant to the application. For candidates with a strong portfolio, this is a useful point to highlight.
The mention of LLM/GenAI exposure as a plus also helps define the ideal fit. It suggests that candidates who have explored newer AI topics may stand out, even though such exposure is not required. This creates a profile of a candidate who is technically grounded, comfortable with applied data work, and open to modern AI tools. The internship appears to reward both academic preparation and practical initiative.
Who the role appears to suit
- Master's degree candidates
- Candidates with Kaggle projects
- Candidates with GitHub projects
- Applicants with exposure to LLM/GenAI
- Those comfortable with Python, Apache Spark, Machine Learning, and Deep Learning
The role is also clearly limited to 2 openings, which means the number of available positions is small. That makes the application process more competitive by nature, even though no selection criteria are described beyond the stated preferences. Since the internship is in Bangalore and in-office, location readiness is another practical factor. Candidates should therefore read the listing as a focused opportunity for technically prepared applicants who can work on-site.
Stipend, Duration, and Hiring Details
The internship offers a stipend of Rs.40,000/month, which is clearly stated in the listing. The duration is 6 months, giving the role a defined time frame. These two details together provide a simple picture of the internship structure: a fixed-term, paid position with a monthly stipend. No other compensation details are mentioned, so the stipend is the only financial information available.
The listing also states that there are 2 openings. This is a useful detail for applicants because it shows the hiring scale is limited. With only two positions available, candidates may want to ensure their application reflects the technical areas and project experience named in the listing. Since the content does not mention any team size, reporting structure, or project allocation, those details should not be assumed.
The application deadline is 3 September 2026, and applications are to be submitted via Internshala. That makes the process straightforward from the information provided. The listing does not include any additional application steps, documents, or screening stages, so those should not be inferred. The safest reading is that candidates should apply through the specified platform before the deadline.
Key hiring facts: 2 openings, Rs.40,000/month stipend, 6 months duration, apply by 3 September 2026 via Internshala.
At-a-glance details
| Detail | Information provided |
|---|---|
| Company | PlaySimple Games |
| Role | Data Science Intern |
| Location | Bangalore |
| Work mode | In-office |
| Stipend | Rs.40,000/month |
| Duration | 6 months |
| Openings | 2 |
| Deadline | 3 September 2026 |
| Application platform | Internshala |
The table above summarizes only the details explicitly provided in the listing. It helps present the internship in a compact format without adding anything beyond the source content. For readers comparing opportunities, the combination of stipend, duration, and location is especially useful. The listing is concise, but the core facts are clear and complete within the provided information.
How the Internship Stands Out
This internship stands out because it combines a strong technical focus with a practical work setting. The role is not framed as a general internship; it is specifically a Data Science Intern position involving real data science and ML problems. That makes it attractive to candidates who want direct exposure to applied work in a company environment. The inclusion of Python, Apache Spark, Machine Learning, and Deep Learning gives the role a broad technical scope.
Another distinguishing feature is the mention of LLM/GenAI exposure as a plus. This indicates that the company is aware of newer AI directions while still grounding the role in established data science practices. The listing also values Kaggle and GitHub projects, which is helpful for candidates who prefer to demonstrate skills through visible work. Together, these points show that the internship rewards both technical knowledge and practical initiative.
The role is also clearly defined in terms of logistics. It is in-office in Bangalore, lasts 6 months, offers Rs.40,000/month, and has 2 openings. The deadline is fixed at 3 September 2026, and the application route is Internshala. These details make the opportunity easy to understand and easy to track for candidates who are planning their applications carefully.
Why the listing is notable
- Focus on real data science and ML problems
- Use of Python and Apache Spark
- Deep Learning included in the scope
- LLM/GenAI exposure recognized as a plus
- Kaggle and GitHub projects valued
- Clear stipend, duration, and deadline details
For candidates who match the stated preferences, the internship offers a focused way to work on applied technical problems in a mobile gaming company. The listing does not overstate the role or add unnecessary complexity, which makes the opportunity easy to evaluate. Anyone considering it can quickly see the core requirements and the practical benefits. That clarity is one of the strongest aspects of the posting.
Frequently Asked Questions
What is the role being offered by PlaySimple Games?
PlaySimple Games is hiring a Data Science Intern. The role is focused on real data science and ML problems. It is an in-office internship based in Bangalore, and the listing identifies the company as a mobile gaming company.
Which skills are mentioned in the internship listing?
The listing mentions Python, Apache Spark, Machine Learning, and Deep Learning. It also says that LLM/GenAI exposure is a plus. In addition, Kaggle and GitHub projects are valued, which makes project-based experience relevant.
Who is preferred for this internship?
A Master's degree candidate is preferred. The listing does not mention any other educational requirement, so this is the only academic preference provided. It also suggests that candidates with relevant projects and technical exposure may be a strong fit.
How many openings are available?
There are 2 openings for the Data Science Intern role. This is the only hiring count mentioned in the content. Since the number is limited, applicants should pay attention to the stated skills, project preferences, and deadline.
What is the stipend and duration of the internship?
The stipend is Rs.40,000/month, and the internship duration is 6 months. These are the only compensation and time-frame details provided. No other pay or duration information is included in the listing.
How and when should candidates apply?
Candidates should apply via Internshala. The application deadline is 3 September 2026. The content does not mention any additional application steps, so the provided platform and deadline are the key instructions.
Conclusion
PlaySimple Games is offering a focused Data Science Intern opportunity in Bangalore for candidates who want hands-on exposure to real data science and ML problems. The role brings together Python, Apache Spark, Machine Learning, and Deep Learning, while also recognizing LLM/GenAI exposure as a plus. With 2 openings, a stipend of Rs.40,000/month, and a 6-month duration, the internship is clearly defined. Candidates who are Master's degree candidates and have Kaggle or GitHub projects may find the listing especially relevant. Applications are due by 3 September 2026 via Internshala.
