Fordham MS Data Science and Quantitative Economics

What is the Fordham MS Data Science and Quantitative Economics?

Fordham MS Data Science and Quantitative Economics is a full-time 30-credit Master of Science for campus study at Lincoln Center. It centres on economic analysis joined with modern data science. Budget USD 141,432, roughly INR 1.36 crore for the minimum-credit route at the latest published rates. Fordham has not issued a 2027-28 price.

The degree moves through economic theory, econometrics, machine learning and applied capstone work. Its final assessed route follows the programme’s published applied or research option. Readers can compare that structure with your earlier study before treating the Fordham brand as sufficient reason to apply. The name doesn’t settle the comparison. This page is written for Fall 2027, while Fordham has not yet published 2027-28 tuition.

How much does the Fordham MS Data Science and Quantitative Economics cost for an Indian student?

The minimum-credit current-rate planning case is USD 141,432, about INR 1.36 crore. It combines Fordham’s latest 2026-27 charges, official New York living categories, health insurance, application where published, SEVIS and the F-1 visa fee. It doesn’t include assigned preparatory or foundation courses and is not a 2027-28 quote.

The table treats the SEVIS and visa charges as separate payments. It does not add a second visa-maintenance total because the complete living plan already covers the study period. Converted at USD 1 = INR 96.00 using ECB reference-rate inputs checked on 8 October 2026. Fordham has not published 2027-28 tuition.

Graduate funding may include assistantships, fellowships, grants and scholarships; availability and conditions vary.Fordham graduate financial support

Tuition uses the latest published 2026-27 gsas graduate tuition and the minimum 30-credit degree plan. Assigned prerequisites sit outside that total. A multi-year route can cost more if Fordham raises later-year rates.

The fee line uses a transparent 3-term planning assumption. The living line prorates Fordham Law’s itemised nine-month New York allowance across 18 months; neither assumption is an individual invoice.

Health insurance is shown separately because a student with approved comparable cover may obtain a waiver. You shouldn’t deduct it until Fordham approves that waiver.

Flights, exchange spreads, a housing deposit and contingency remain outside the table. You can’t reduce the total for scholarships until there is a written award.

Fordham has not published 2027-28 tuition. Refresh every charge against the student account and school fee page before enrolment.

Can an Indian prospective student meet Fordham MS Data Science and Quantitative Economics entry rules?

The review starts with the exact programme requirements. Fordham assesses a recognised prior degree, preparation in intermediate microeconomics and macroeconomics, calculus, linear algebra, statistics and Python, the school-specific English evidence and every listed document. General university wording can’t replace a higher programme rule. Check gaps explicitly.

Missing economics, mathematics, statistics or Python prerequisites can become non-degree preparatory work in or before the first term and therefore change cost and workload.

The first transcript audit should find concrete proof of economic theory. A useful audit records the module title, mark, credit weight and syllabus topic so an assessor does not have to infer readiness from the institution name.

Next, isolate proof for econometrics. A laboratory, project or substantial assignment is stronger than a list of buzzwords because it shows what was built, measured or decided and what limitations remained.

The statement should explain why machine learning is the next academic step and why Fordham’s applied capstone work route serves it. Repeating the master’s webpage does not answer that personal progression question.

Finally, English, recommendations and translations remain independent document checks. A file that clears the academic match can remain incomplete if an accepted score, literal translation or required referee response is missing.

MS Data Science and Quantitative Economics uses ECON 6010 Microeconomic Theory I as a 3-credit checkpoint. Readiness for economic theory is visible before ECON 6010 Microeconomic Theory I, not repaired automatically by enrolment. A transcript item, syllabus topic and assessed result together make that preparation easier to recognise.

MS Data Science and Quantitative Economics uses ECON 6020 Macroeconomic Theory I as a 3-credit checkpoint. Readiness for econometrics is visible before ECON 6020 Macroeconomic Theory I, not repaired automatically by enrolment. A transcript item, syllabus topic and assessed result together make that preparation easier to recognise.

MS Data Science and Quantitative Economics uses ECON 6910/6950 Applied Econometrics or Financial Econometrics as a 3-credit checkpoint. Readiness for machine learning is visible before ECON 6910/6950 Applied Econometrics or Financial Econometrics, not repaired automatically by enrolment. A transcript item, syllabus topic and assessed result together make that preparation easier to recognise.

MS Data Science and Quantitative Economics uses CISC 5790 Data Mining as a 3-credit checkpoint. Readiness for applied capstone work is visible before CISC 5790 Data Mining, not repaired automatically by enrolment. A transcript item, syllabus topic and assessed result together make that preparation easier to recognise.

MS Data Science and Quantitative Economics uses CISC 5800 Machine Learning as a 3-credit checkpoint. Readiness for economic theory is visible before CISC 5800 Machine Learning, not repaired automatically by enrolment. A transcript item, syllabus topic and assessed result together make that preparation easier to recognise.

Within MS Data Science and Quantitative Economics, the relationship between economic theory and machine learning is a readiness test for economic data scientist ambitions. A file showing only econometrics leaves the applied capstone work part of this academic progression unexplained.

A future applied researcher still needs documented preparation in intermediate microeconomics and macroeconomics, calculus, linear algebra, statistics and Python. For MS Data Science and Quantitative Economics, career intent cannot substitute for that academic base, while the academic record remains one part of a broader selection model.

MS Data Science and Quantitative Economics preparation check 1 connects economic theory with ECON 6010 Microeconomic Theory I. Name assessed work, the method used and the result an admissions reader can verify rather than listing a subject without evidence.

MS Data Science and Quantitative Economics preparation check 2 connects econometrics with ECON 6020 Macroeconomic Theory I. Name assessed work, the method used and the result an admissions reader can verify rather than listing a subject without evidence.

MS Data Science and Quantitative Economics preparation check 3 connects machine learning with ECON 6910/6950 Applied Econometrics or Financial Econometrics. Name assessed work, the method used and the result an admissions reader can verify rather than listing a subject without evidence.

MS Data Science and Quantitative Economics preparation check 4 connects applied capstone work with CISC 5790 Data Mining. Name assessed work, the method used and the result an admissions reader can verify rather than listing a subject without evidence.

MS Data Science and Quantitative Economics preparation check 5 connects economic theory with CISC 5800 Machine Learning. Name assessed work, the method used and the result an admissions reader can verify rather than listing a subject without evidence.

Three checks that can block a MS Data Science and Quantitative Economics application

1. A profile indicator is not an offer promise

   Fordham publishes holistic review rather than a universal admission GPA floor for this programme. Review can still distinguish candidates through subject depth, statement quality, recommendations and the completed file.

2. The degree title cannot prove prerequisites

   A broad Indian degree name may hide whether intermediate microeconomics and macroeconomics, calculus, linear algebra, statistics and Python was studied. Add syllabi or official descriptions when course titles do not make the preparation clear.

3. English rules can be master's-specific

   The working reference is IELTS 7.0 with 6.5 in each band, or another published equivalent. Fordham says individual programmes may set higher rules or restrict test formats, so the exact degree page controls.

How should an Indian applicant apply for Fordham MS Data Science and Quantitative Economics?

Apply through Fordham’s school-specific graduate route. 8 January 2027 priority consideration deadline. Submit earlier for credential evaluation, funding evidence, I-20 production and visa preparation. Indian records can also need transcript clarification, so leave enough time to answer a school request before the published cut-off.

Select the exact campus programme, upload academic and programme documents, pay the application fee, monitor the applicant portal, clear offer conditions, document funding, and complete the I-20 and F-1 process.

The allowances are Nbyula planning estimates, not processing times published by Fordham University.

Build the file around Microeconomic Theory I and Macroeconomic Theory I, not around a generic Fordham statement. Applicants can use earlier coursework or employment to show readiness, then identify the gap that the published curriculum is meant to close.

The programme reports 8 january 2027 priority consideration deadline. A priority date can be followed by space-available review, while a final date closes the published window. Neither should be confused with the separate international I-20 timing needed to reach campus.

After admission, read the offer and my.fordham task list line by line. Financial guarantee, final transcripts, immunisation records and I-20 processing can each continue after the academic decision and can each delay enrolment if ignored.

For F-1 planning, check the SEVIS I-901 step and the US visa fee page directly. Fee payment does not guarantee a visa, and a programme offer does not replace consular review.

What jobs can follow Fordham MS Data Science and Quantitative Economics?

The academic map supports directions such as economic data scientist, quantitative consultant, policy analyst and applied researcher. The university presents this course as STEM designated. The OPT framework is work authorisation rather than a placement or sponsorship guarantee. Each direction still needs role-specific, inspectable work samples.

These are academic map-linked directions for MS Data Science and Quantitative Economics, not a measured probability of employment, salary, visa sponsorship or promotion.

For a economic data scientist application, preserve the brief, inputs, method, decisions and limitations from Microeconomic Theory I. That record gives a recruiter something more reliable than a transcript line or a claim that the degree was practical.

The quantitative consultant route needs a different proof item from Macroeconomic Theory I. Explain the trade-off made, the proof rejected and the effect of uncertainty so the work shows judgement rather than only tool familiarity.

A candidate aiming at policy analyst should use the culminating assessment to join both samples around one problem. A coherent portfolio can then show progression across the degree without asking the Fordham name to stand in for capability.

F-1 graduates can normally seek up to 12 months of OPT, and an eligible STEM degree may support a further 24-month extension if every rule is met. The USCIS STEM-OPT guidance controls that process and does not require any employer to hire the graduate.

Inside MS Data Science and Quantitative Economics, ECON 5710/CISC 5450 Mathematical Analysis in Economics or Mathematics for Data Science carries 3 published credits. Its value for a economic data scientist direction depends on making econometrics inspectable. A retained question, method, result and limitation can show what ECON 5710/CISC 5450 Mathematical Analysis in Economics or Mathematics for Data Science added without implying a promised hiring result.

Inside MS Data Science and Quantitative Economics, Three approved economics/data-science electives carries 9 published credits. Its value for a quantitative consultant direction depends on making machine learning inspectable. A retained question, method, result and limitation can show what Three approved economics/data-science electives added without implying a promised hiring result.

Inside MS Data Science and Quantitative Economics, CISC/ECON 6080/6081/6085-6086 Capstone, practicum or thesis option carries 3 published credits. Its value for a policy analyst direction depends on making applied capstone work inspectable. A retained question, method, result and limitation can show what CISC/ECON 6080/6081/6085-6086 Capstone, practicum or thesis option added without implying a promised hiring result.

A possible economic data scientist direction needs inspectable work from this requirement: ECON 5710/CISC 5450 Mathematical Analysis in Economics or Mathematics for Data Science. Course credit is not a hiring promise; retain an artefact that shows the question, method, result and limitation.

A possible quantitative consultant direction needs inspectable work from this requirement: Three approved economics/data-science electives. Course credit is not a hiring promise; retain an artefact that shows the question, method, result and limitation.

A possible policy analyst direction needs inspectable work from this requirement: CISC/ECON 6080/6081/6085-6086 Capstone, practicum or thesis option. Course credit is not a hiring promise; retain an artefact that shows the question, method, result and limitation.

A possible applied researcher direction needs inspectable work from this requirement: ECON 6010 Microeconomic Theory I. Course credit is not a hiring promise; retain an artefact that shows the question, method, result and limitation.

A possible economic data scientist direction needs inspectable work from this requirement: ECON 6020 Macroeconomic Theory I. Course credit is not a hiring promise; retain an artefact that shows the question, method, result and limitation.

Who is Fordham MS Data Science and Quantitative Economics for, and who should avoid it?

A strong fit wants assessed progression in economic theory and machine learning, accepts full-time study at Lincoln Center and can fund the plan without guaranteed US earnings. A weak fit needs extensive prerequisite repair, another delivery mode or a placement promise Fordham does not make.

The next fit question concerns Macroeconomic Theory I. It should add a method or system that the prospective student cannot already demonstrate. If it mostly repeats a strong undergraduate module, examine the elective freedom before paying for the overlap.

The professional test is whether a economic data scientist hiring manager can inspect output from machine learning. A useful artefact states the problem, data or constraints, the chosen method, the result and the limits of that result.

Someone pursuing quantitative consultant work must also value applied capstone work. If that part of the degree consumes substantial assessed time but has little use in the intended role, a differently structured master’s may be the better buy.

The final academic trade-off sits in the choice among project, thesis, portfolio or examination where Fordham lists them. A thesis serves research depth, an applied project serves delivery proof, and a portfolio serves synthesis. Only routes actually published for this master’s belong in the decision.

Affordability is separate from academic fit. The estimate uses USD 1 at INR 96.00, so exchange movement changes the rupee amount even when Fordham leaves a dollar charge unchanged.

The campus choice also matters. This page uses Lincoln Center and in-person study. An prospective student selecting an online version would face different attendance, visa and work-authorisation consequences and should not reuse this page’s F-1 assumptions.

Applicants can ask current MS Data Science and Quantitative Economics students about access to preferred electives, team formation, faculty supervision and the weekly load. The research pass did not locate three independent exact-master’s accounts, so those lived details remain questions rather than reported facts.

For a future quantitative consultant, fit check 1 asks what new decision econometrics makes possible. MS Data Science and Quantitative Economics adds value only when that result changes the evidence already in the application file.

For a future policy analyst, fit check 2 asks what new decision machine learning makes possible. MS Data Science and Quantitative Economics adds value only when that result changes the evidence already in the application file.

For a future applied researcher, fit check 3 asks what new decision applied capstone work makes possible. MS Data Science and Quantitative Economics adds value only when that result changes the evidence already in the application file.

For a future economic data scientist, fit check 4 asks what new decision economic theory makes possible. MS Data Science and Quantitative Economics adds value only when that result changes the evidence already in the application file.

For a future quantitative consultant, fit check 5 asks what new decision econometrics makes possible. MS Data Science and Quantitative Economics adds value only when that result changes the evidence already in the application file.

What does the Fordham MS Data Science and Quantitative Economics curriculum contain?

The official Fordham programme page sets the 30-credit degree and its named requirement blocks. The table preserves those published components and alternatives; it does not claim that every student completes every listed option. Applicants can use it to test sequence, prerequisites and elective room against the capability you still need.

The note “Published degree-plan component” applies to 8 components in this table.

• Complete 30 approved graduate credit hours.
• Follow the published choice among a capstone, practicum or co-mentored thesis.
• Confirm approved electives, prerequisites and the plan of study with the academic unit.

Applicants can use the required sequence to establish readiness for Microeconomic Theory I, then choose electives that deepen machine learning instead of creating several disconnected introductions. The official plan of study remains the authority for what can count together.

Fordham can revise course availability and approved lists. Recheck every code, credit value, campus offering and culminating route before accepting an offer, especially where the catalogue publishes an area rather than a closed list of named electives.

Should an Indian prospective student shortlist the Fordham MS Data Science and Quantitative Economics?

Shortlist the Fordham MS Data Science and Quantitative Economics when its full-time 30-credit structure and work in economic theory close a documented capability gap. Keep it off the list when the budget depends on uncertain income or the degree would mostly repeat prior study.

The decision turns on whether machine learning and the final assessment can create work relevant to a economic data scientist or quantitative consultant conversation. Fordham's name is not a substitute for that match.

You shouldn't choose MS Data Science and Quantitative Economics for the Fordham name or work-authorisation assumptions alone. The 30-credit curriculum must justify the INR 1.36 crore planning case, and Fordham publishes no guaranteed job, salary or sponsorship outcome for this exact degree. That promise won't come from the course page.

Sources

These sources support the programme, admission, cost and immigration information used on this page.

Sources checked on October 8, 2026. Current intake information follows. Fall 2027 full-time campus route.