AKS Tech Data Science Internship: Paid Work-From-Home Opportunity
AKS Tech has advertised a three-month Data Science internship on Internshala with a monthly stipend of ₹25,000–30,000. The opportunity is work from home and covers predictive modelling, data analysis, natural language processing, deep learning and AI-related projects. The listing gives 23 October 2026 as the application deadline and identifies four openings. Candidates must be available for the complete internship and have relevant skills and interests.
This is an employer advertisement on Internshala, not a placement guarantee or an independently verified claim about the employer’s working conditions. The advertised work and compensation are summarised below so applicants can judge the fit and ask informed questions before accepting an offer. A possible permanent role is mentioned, but conversion is conditional and must not be confused with the internship stipend.
Key details at a glance
- Organisation: AKS Tech, described in its listing as an IT services and consulting firm based in Noida.
- Role: Data Science intern.
- Work mode: Work from home.
- Duration: Three months.
- Advertised stipend: ₹25,000–30,000 per month.
- Openings: Four.
- Application deadline: 23 October 2026.
- Joining availability: Between 23 September and 28 October 2026.
- Listed benefits: Certificate, recommendation letter, flexible work hours, a five-day workweek and a possible job offer.
What the internship involves
The first responsibility is working with the data science team to develop and implement machine-learning models for predictive analytics. The advertisement does not specify a particular industry dataset, model family or production stack. Applicants should therefore avoid assuming that the assignment will exclusively involve generative AI, financial forecasting or any other specialisation. The actual project scope should be confirmed with the hiring team.
A second component is analysing complex datasets to identify trends and insights that can inform business strategy. This connects technical analysis with a practical business question. The listed work is not limited to training a model: it also includes interpreting information and contributing to decisions. An applicant who can explain why a pattern matters, as well as how it was calculated, has a relevant example to discuss.
Cross-functional collaboration is another stated responsibility. Interns are expected to contribute to data-driven solutions across projects, rather than work entirely in isolation. The employer also lists natural language processing to extract useful information from unstructured sources, assistance with developing and optimising deep-learning algorithms, and research into AI-based solutions for business problems. These are the advertised areas of work, not a promise that every intern will complete a project in every area.
The description further asks interns to follow developments in data science and use that knowledge to improve processes and products. This suggests a role that combines implementation with ongoing learning. However, the listing does not describe a formal teaching syllabus, guaranteed training hours, named mentors or assessment timetable. Candidates looking primarily for a structured classroom-style course should clarify how supervision and learning support will work.
Skills and eligibility
The skills named in the advertisement are Python, SQL, Data Analytics, Data Science, Machine Learning, Natural Language Processing, Deep Learning and Artificial Intelligence. The eligibility section requires relevant skills and interests, availability for remote work, the ability to join within the stated start window, and a commitment of three months. It does not publish a specific degree, graduation batch, minimum percentage or age limit.
That absence should not be converted into an unsupported claim that every applicant will qualify. The employer may assess technical ability during recruitment. Students and graduates should compare their actual experience with the responsibilities and describe it accurately. Someone who has completed a small Python analysis project should not claim professional deep-learning expertise simply because deep learning appears among the advertised skills.
The five-day workweek and flexible hours are listed perks. Exact daily hours, required overlap with the team, equipment support and arrangements for examination periods are not specified. Work from home does not automatically mean part-time, self-paced or available from every country. Applicants should confirm these details, particularly if they intend to combine the internship with college classes or another commitment.
Stipend and possible permanent conversion
The advertised internship stipend is ₹25,000–30,000 per month. Unlike some listings that split a headline figure into fixed pay and incentives, this advertisement does not provide a separate fixed-versus-variable breakdown. The exact amount offered to an individual candidate, payment dates, deductions if any, and attendance or performance conditions should be obtained in writing before joining.
The additional-information section states that, on successful conversion to a permanent employee, a candidate can expect an annual salary of ₹6,50,000–7,00,000. This is a potential post-internship salary, not the amount paid during the three months. The advertisement does not guarantee conversion for all four selected interns or specify a conversion percentage. Treat the internship and any later employment decision as separate stages.
A certificate and letter of recommendation are also advertised. Their issue criteria and timing are not detailed. These benefits may matter to students seeking recognised evidence of experience, but they should not replace scrutiny of the actual work, supervision and written compensation terms. No applicant should interpret the presence of a certificate as a guarantee of academic credit from their college.
How to apply
- Open the AKS Tech Data Science internship listing on Internshala.
- Confirm the employer name, remote work mode, three-month duration and current application status.
- Sign in or register on the platform if required, then review the application questions shown for this listing.
- Update your resume and profile with relevant technical skills, projects and accurate availability.
- Submit through the listing before 23 October 2026 and retain the application confirmation or platform record.
The last date for applications and the latest date in the joining window are different. A start date extending to 28 October does not mean applications remain open until that date. The advertisement does not state a closing hour or describe the selection rounds. Use the current listing for any changes and respond to legitimate follow-up messages through the recruitment channel.
Practical application preparation
The following suggestions are editorial preparation advice, not additional employer requirements. Choose one or two projects that match the responsibilities and explain the underlying question, dataset, cleaning decisions and result. A concise, reproducible analysis is more informative than a long list of algorithms without evidence of use. If a project is academic or self-directed, label it that way.
For a predictive-modelling example, be ready to explain how training and evaluation data were separated, which metric was used and what limitations remain. For an NLP example, describe the text source and how it was prepared. For SQL or analytics work, show how the query or calculation answers a useful question. Do not publish confidential datasets or work belonging to a previous employer in a portfolio.
Applicants with uneven experience across the advertised skills can distinguish what they have used independently, what they have studied and what they want to learn. This helps the recruiter assess fit without inflated claims. Before accepting an offer, ask who will review your work, what an initial assignment looks like and how progress will be assessed during the three-month period.
Important checks before joining
Confirm the employing entity, reporting contact, stipend, working hours and role scope in the offer documentation. The source for this opportunity is the employer’s Internshala advertisement; publication here does not certify the employer’s payment history or guarantee selection. Be cautious of unexpected requests to pay for placement or compulsory training, and use the platform’s reporting channels if the recruitment terms differ materially from the advertisement.
This opening is most relevant to applicants seeking a paid remote internship with exposure to data science and AI-related work, who can commit for three months and demonstrate relevant skills. Recheck the live advertisement before submitting, because availability, start arrangements and advertised terms may change after this summary was prepared.
