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Data Jobs: Where the Better Pay and Flexibility Sit
Across 200 data listings, average pay reaches $64,501 and only 19% are remote, so target senior AI and engineering work first.
Average listed pay reaches $58,001 to $64,501. That is the useful number in this 200-listing data science and analytics snapshot. The higher end is tied to specialist AI, data engineering, and senior technical work, not generic analyst titles. As the salary chart shows, you should aim above entry-level analyst searches if pay is the main goal.
The listings also show a split market: only 19% are remote, while the largest named employers are Mercor, Datamatics Technologies, Qureos Inc, HR POD - Hiring Talent Globally, and foodpanda. Night-shift pay cannot be measured from the supplied data, and the listings do not provide a location count, so claims about a night premium or the busiest city would be guesswork.
Top Employers by Listing Count
Position Types
Salary Range
Where the money sits
The pay range tells you how to search. A Senior Data Scientist, Lead Data Engineer, Principal AI Solution Expert, or AI Research Engineer is more likely to sit near the upper end than a broad Data Analyst listing. The dataset does not attach individual salaries to each card, so nobody can honestly name one employer as the highest payer from these records alone.
That still gives you a practical filter: search senior, lead, principal, AI, cloud, and platform terms before spending time on general analyst adverts. The remote listings also include specialist work, including agentic post-training, multimodal vision, and adversarial AI. Those titles point toward technical screening and deeper model knowledge rather than basic spreadsheet reporting.
For market context, use the U.S. Bureau of Labor Statistics data scientist page when checking how the listed pay compares with broader published benchmarks. The listing dataset is a snapshot, not a guarantee of an offer.
AI Research Engineer
A 100% remote worldwide AI Research Engineer listing is the clearest flexibility play in the set. The title points to agentic post-training, so applicants should expect hands-on model work rather than routine dashboard maintenance. Pick it if you already have research or machine-learning depth and need location freedom; do not treat the remote label as proof of easy access.
AI Research Engineer
Multimodal and vision work sits in the same specialist lane but covers a different technical problem from agentic post-training. The worldwide remote wording widens the geographic reach, while the research title raises the skill bar. Apply here ahead of a general analyst advert if computer vision or multimodal systems is already in your toolkit.
Principal AI Solution Expert
Principal AI Solution Expert is the seniority outlier among the supplied titles. It suggests architecture, client-facing technical judgment, and ownership beyond model experimentation, although the listing data does not state salary or benefits. This suits someone who has moved past individual contributor delivery and can explain AI systems to decision-makers.
Lead Data Engineer
Lead Data Engineer focused on an AWS data platform gives experienced infrastructure candidates a more concrete route than the research titles above. The AWS reference signals cloud pipeline work, so check your production data engineering experience before applying. Choose this over an AI research advert if building dependable platforms is your stronger trade.
Senior Data Scientist
Senior Data Scientist is the most direct match for people who want analytics and modelling without committing to a narrowly named AI research track. The senior label matters because the dataset average is already high at $58,001 to $64,501. Use this search lane if you can show shipped models, experiments, and business results rather than only coursework.
The five cards above are not proof that one employer pays more than another; the source data does not connect salary figures to individual listings. They do show where the strongest salary signals are: seniority, cloud ownership, and specialist AI. Before applying, verify the live advert and employer details through the Talent.com Pakistan listings page or the source named in the advert.
Who is actually hiring?
Mercor, Datamatics Technologies, Qureos Inc, HR POD - Hiring Talent Globally, and foodpanda are the five most visible company names in the aggregate data. That mix matters. It is not just a research market; it includes technology services, global hiring, and a consumer platform that may need analytics tied to operations and products.
Use employer names as a starting point, not a salary ranking. The data gives no company-by-company pay table, and it does not show how many of the 200 listings belong to each employer. Search each company alongside the exact title, then check whether the advert is direct hire, contract, or freelance before sending your CV.
Hadoop Data Engineer
Hadoop Data Engineer is an older-school data platform title compared with the AI-heavy cards above, but that can be useful if your strength is distributed processing and production systems. The Faisalabad listing location is supplied in the card, yet no location totals are available across the dataset. Apply when your Hadoop experience is real and recent enough to discuss operations, not just training projects.
Data Analyst
Data Analyst is the broadest title in the group and likely the easiest search term for candidates moving into analytics. It also carries less seniority signal than the engineering and AI cards, so use a portfolio to compete: SQL work, clear reporting, and a measurable business result. This is the sensible route for a capable analyst who is not ready to claim principal-level ownership.
Adversarial AI Specialist
The adversarial AI listing is the clearest hourly-pay reference in the supplied items, with pay up to $22 per hour and fully remote work. That ceiling is far below the aggregate annual range, so compare the maths before choosing flexibility over seniority. It fits someone testing AI work or needing remote hours, not a candidate chasing the highest long-term salary.
The job-type breakdown adds another warning. The data records 25 listings as Full-time and 21 as full_time, plus 12 contract, 3 Part-time, 2 part_time, 2 freelance, 1 Internship, and 1 Full-time and Internship. The capitalisation differences look like separate labels, but they should not be treated as different employment markets without cleaning the source first.
Even with that limitation, full-time labels clearly dominate the named categories. Contract and freelance work are present but much smaller. If you need stable income, start with full-time searches. If you are building a portfolio, the $22-per-hour adversarial AI listing shows a flexible route, but its stated ceiling should not be compared directly with annual senior salaries.
What the data cannot prove
Night-shift pay is not available here. None of the supplied records identifies a night shift, shift differential, or overtime rate, so there is no honest answer on whether nights pay a premium. Ask the employer directly about hours, time-zone coverage, weekend work, and overtime before accepting an interview.
Location opportunity is also unranked. Individual cards mention Karachi, Mingora, Faisalabad, Gujranwala, Bahawalpur, and Multan, but the aggregate data does not count listings by city. Treat Karachi, Gujranwala, and the other named places as examples, not winners. Remote worldwide adverts may matter more than city totals if relocation is off the table.
The practical move is simple: filter first by seniority and technical area, then by employment type and location. Check the employer's own careers page where available, compare the live advert with the listing summary, and never assume the aggregate salary range applies to every title.
SDK Engineer
SDK Engineer is adjacent to data engineering rather than a pure analytics job, so it belongs on the edge of this comparison. The title points to developer tooling and software integration, not a standard analyst workload. Keep it on your list only if you can build and maintain developer-facing systems; otherwise, the Data Analyst card is a cleaner match.
What to do next
Start with the salary target: the aggregate range is $58,001 to $64,501, so search senior AI, data engineering, cloud, and principal titles before broad entry-level terms. Next, decide how much flexibility is worth. Only 19% of the 200 listings are remote, and the remote examples range from high-skill research work to an advert capped at $22 per hour.
For a senior technical candidate, I would start with the AI Research Engineer, Principal AI Solution Expert, Lead Data Engineer, and Senior Data Scientist searches. For someone entering the field, use Data Analyst and build evidence around SQL, Python, dashboards, and one finished project. For immediate remote income, inspect the adversarial AI listing carefully, but compare its hourly ceiling with the annual range before treating it as a long-term move.
The short version: target specialist titles for pay, verify employers instead of guessing from brand names, and ask about shifts and location because this dataset does not answer those questions. Forge your next career with the details checked before you apply.
