Leading Macro Hedge Fund - Macro Econometrics Algorithm Developer (Real-Time NLP Focus) - New York

[Recruiter-Jim]

Leading Macro Hedge Fund - Macro Econometrics Algorithm Developer (Real-Time NLP Focus) - New York

This role centers on the development of real-time NLP algorithms, with a strong emphasis on applying advanced econometric techniques to macroeconomic data. You'll design and implement data pipelines to ingest and process diverse data sources, focusing on the econometric modeling of real-time data for predictive insights. A key responsibility involves translating these analyses into actionable investment strategies, leveraging sophisticated econometric models such as Factor Models, Panel Data Models, and Time Series Models.

The ideal candidate will possess a deep understanding of econometric theory and its application to financial markets, evidenced by a top-tier GPA from a Master’s degree program in Econometrics, Economics, obtained from a top-tier university. They will have 2-6 years of experience within a bank, hedge fund, or central bank.

Skills:

• Econometric Modeling (Factor Models, Panel Data Models, Time Series Models, Generalized Linear Models, Linear Regression)
• Python Proficiency (NumPy, Pandas, Scikit-learn, Statsmodels, Stan)
• Natural Language Processing Libraries (NLTK, spaCy, Transformers).
• Natural Language Processing Algorithms: Sentiment analysis algorithms, Topic modeling (LDA), Word embeddings, Named entity recognition
• Data Pipeline Design and Implementation (ETL, API integration for data retrieval)
• Financial Market Data Analysis (including alternative data)
• Time Series Data Structures: Efficient storage and manipulation of time-stamped data, crucial for real-time analysis. Examples include specialized time series databases or optimized in-memory representations.
• Queues and Stacks: Used for managing incoming data streams and processing them in a specific order, essential for real-time data pipelines.
• Hash Tables: For rapid lookups and data retrieval, vital for processing large datasets and identifying patterns in real-time.
• Trees (e.g., Tries): Useful for efficient text processing and searching, particularly in NLP applications involving real-time analysis of textual data.
• Graphs: To represent relationships between data points, enabling the analysis of complex networks and dependencies in financial markets.
• Priority Queues: For managing and processing events or data points based on their priority, critical for real-time decision-making in trading.

Compensation range: $350k-$500k

Send your resume to James@njf.com

 

[NIHARMAHESHJANI]

Dear Recruiter-Jim,
I am intersted on this job:

Why I’m a Strong Fit

1. Technical Expertise:
* Python/C++: Built low-latency ML models (e.g., EV range prediction at Trickce, 92% accuracy) and optimized algorithms (40% speedup in Brain Tumor Segmentation, LOR Nihar.Rhythm Agrawal.pdf ).
* Quantitative Modeling: Statistical analysis of socioeconomic drivers of Kalazar Disease (logistic regression) and derivatives pricing coursework (Columbia Financial Engineering certification, Certificates_List_Nihar_Mahesh_Jani.docx ).

2. Relevant Experience:
* CTO (Tech Lead ) , Trickce: Led on-device AI model development for EV performance prediction, balancing real-time data processing and risk mitigation. ( Nihar J. on LinkedIn: #startups #innovation #googleforstartups #iima #trickee #innovation… )
* Internships: Researched accessible tech solutions (Birmingham City University, BCU Offer Letter.pdf ) and engineered computer vision pipelines (Kalindi Engineering).

3. Academic Rigor:
* I scored an impressive 99.17th percentile in JEE Mains Mathematics( LETTER OF RECOMMENDATION-Nihar.pdf ), ranking among the top 0.83 percentile out of 12 lakh students. This achievement is particularly noteworthy as JEE Mains serves as a crucial entrance exam for prestigious NITs and IITs. Additionally, I have secured certifications in Machine Learning from Stanford University and have completed coursework in Applied Linear Algebra, Probabilistic Graphical Models, and Human-Computer Interaction (HCI). ( Certificates_List_Nihar_Mahesh_Jani.docx )

I also possess excellent communication and teamwork skills. I served as the Secretary of the IEEE Ahmedabad University Student Branch for a year, from March 1, 2023, to March 2024. During my tenure, I spearheaded events related to Artificial Intelligence (AI), Machine Learning (ML), Cybersecurity, Deep Learning, Internet of Things (IoT), and career-related services. Additionally, I invited renowned personalities for their prestigious talks. Furthermore, I worked at two Non-Governmental Organizations (NGOs): Green Bhumi Foundation and Prabhat Education Foundation.
( EXTRA_CURRICULAR_ACTIVITIES.pdf )

Why This Internship?
I aim to bridge my technical foundation with hands-on quant experience before starting at Rutgers. My goal is to contribute to impactful projects—whether in algorithmic trading, risk modeling, or data-driven strategy development—while learning from industry experts like yourself.

Proof of my 99.17th percentile rank in JEE Mains Mathematics, placing me among the top 0.83 percentile out of 12 lakh students: ( LETTER OF RECOMMENDATION-Nihar.pdf )



I would welcome the chance to discuss how my skills align with your team’s needs. Thank you for considering my application.

Any referral from you would be incredibly helpful to me and would greatly benefit my career. I would be very grateful for your assistance.

Best regards,
Nihar Mahesh Jani
niharmaheshjani@gmail.com | +91 6352516405
LinkedIn: https://www.linkedin.com/in/nihar-j-8824011bb |
GitHub: NiharJani2002 - Overview