Quantitative Researcher | Data Scientist | Time-Series & Options Modeling Expert | IIT + Cornell | Python | Julia | SQL

Aarav Mehta

Professional Summary

Quantitative Researcher skilled in time-series analysis, options pricing, and statistical arbitrage. Experienced in Python, Julia, R, and financial data tools with published research in computational biology and genetics.

Work Experience

Quantitative Research Intern – Statistical Arbitrage at Greenland Investment Management

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Backtested crude oil arbitrage strategies using Python and SQL; improved alpha strategy performance and market neutrality with Bloomberg and WIND.

Undergraduate Researcher – Computational Systems Biology at Indian Institute of Technology Guwahati

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Modeled cellular dynamics with Julia; reduced breast cancer morphospace dimensionality using t-SNE, UMAP; published findings on epithelial-mesenchymal transition.

MITACS Research Intern – Statistical Genetics at University of Western Ontario

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Analyzed GWAS and scATAC-seq data using regression and ComputeCanada; published on improving cell-type detection with single-cell chromatin accessibility data.

Education

MS in Data Science and Biostatistics

Cornell University

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GPA: 3.89 / 4.00

B.Tech in Biotechnology

Indian Institute of Technology Guwahati

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GPA: 8.49 / 10.00

Skills

Technical Skills

  • Python
  • C/C++
  • R
  • MATLAB
  • Julia
Score
82/100
Education
88/100
Projects
78/100
Skills
80/100
Work Experience
75/100
Profile
80/100
Certifications
0/100
Header
85/100
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Strong quantitative and programming skills across Python, Julia, R, and SQL.
Dual degrees from prestigious institutions with relevant coursework in data science and biotechnology.
Demonstrated research publication experience in computational biology and genetics.
Proven competitive success in quant challenges and Olympiads showcasing problem-solving and analytical abilities.

Education

88%
Strong academic background with top-tier institutions and relevant coursework supporting the candidate’s expertise.
Including GPA and coursework is valuable; consider adding honors or notable projects to further strengthen this section.

Projects

78%
Projects are well-aligned with the candidate’s field and demonstrate practical application of skills.
Include specific outcomes or performance metrics (e.g., accuracy improvements, returns generated) to highlight impact.
Clarify the scale or scope of projects to provide better context.

Skills

80%
Comprehensive list of hard skills and tools relevant to quantitative research and data science, enhancing keyword coverage.
Consider grouping skills into categories (e.g., Programming Languages, Tools, Libraries) for better ATS parsing.
Add relevant soft skills such as 'Problem Solving' or 'Analytical Thinking' to showcase well-rounded capabilities.

Work Experience

75%
Experience descriptions include relevant technical tools and domain-specific projects, which is good for ATS keyword matching.
Add quantifiable results or impact metrics (e.g., percentage improvements or returns) to demonstrate effectiveness.
Use consistent formatting for dates and employment types; clarify current employment status for the ongoing internship.
Expand on responsibilities and achievements to provide more context and depth.

Profile

80%
Summary clearly states skills and domain expertise; consider adding more quantifiable achievements to increase impact.
Profile highlights are well-structured but could benefit from bullet points in the main summary for better ATS parsing and readability.
Add a brief objective or career goal to clarify candidate's direction.

Certifications

0%
Section missing

Header

85%
Strong headline with relevant keywords like 'Quantitative Researcher', 'Data Scientist', and technical skills which improve ATS matching.
Include a professional LinkedIn or GitHub URL to enhance recruiter access and ATS parsing.
    Quantitative Researcher | Data Scientist | Time-Series & Options Modeling Expert | IIT + Cornell | Python | Julia | SQL | Aarav Mehta | Resume Template - Yotru