Employment Type: Full-Time
Function: Quantitative Research
Location: New York / Remote

We are building a focused research team that values intellectual rigor, empirical thinking, clear communication, and the willingness to challenge assumptions.

The Role

We are looking for a Quantitative Researcher to develop, test, and validate analytical models across complex datasets and decision environments.

You will work across the full research lifecycle—from framing hypotheses and identifying relevant data to designing models, testing robustness, interpreting results, and communicating conclusions.

This role is well suited for someone who enjoys working at the intersection of statistics, computation, and real-world problem solving. We care less about using the most complicated methodology and more about selecting the right methodology for the question.

What You’ll Do

• Design and conduct quantitative research from hypothesis formation through validation

• Analyze large, noisy, and multidimensional datasets to identify meaningful patterns and relationships

• Develop statistical, econometric, and computational models

• Conduct time-series and cross-sectional analysis

• Build forecasting, simulation, and scenario-analysis frameworks

• Evaluate model performance using appropriate in-sample and out-of-sample methodologies

• Conduct sensitivity analysis, robustness testing, and alternative specification testing

• Identify sources of model instability, bias, or uncertainty

• Build reproducible research workflows and analytical tools

• Translate quantitative findings into clear conclusions and decision-relevant insights

• Document assumptions, methodologies, limitations, and results

• Collaborate with researchers working across AI, risk, and decision analytics

• Continuously refine models as new data and evidence become available

What We’re Looking For

• Bachelor’s, Master’s, or PhD in statistics, mathematics, computer science, engineering, economics, operations research, quantitative finance, or another highly quantitative discipline

• Strong foundation in probability, statistics, and quantitative modeling

• Strong Python programming skills

• Experience working with real-world datasets

• Ability to distinguish statistical significance from practical relevance

• Strong understanding of model validation and experimental design

• Ability to independently structure ambiguous analytical problems

• Strong written and verbal communication skills

• High level of intellectual curiosity and attention to detail

• Willingness to challenge your own assumptions when the evidence changes

Preferred Qualifications

• Experience with time-series modeling, forecasting, optimization, simulation, or causal inference

• Familiarity with SQL and modern data workflows

• Experience with financial, economic, operational, or other high-dimensional datasets

• Exposure to machine learning techniques

• Experience conducting independent academic or industry research

• Publications, working papers, research projects, GitHub repositories, or other examples of quantitative work

Apply: Send your resume and relevant research, portfolio, GitHub, or writing sample to careers@alphatopiaresearch.com

Employment Type: Full-Time
Function: Artificial Intelligence / Research Engineering
Location: New York / Remote

The Role

We are looking for an AI Research Engineer to build, evaluate, and improve applied AI systems used in research and analytical workflows.

You will work across machine learning, large language models, information retrieval, model evaluation, structured data extraction, experimentation, and human-machine decision support.

This role sits between research and engineering. You should be comfortable reading technical literature, designing experiments, writing production-quality code, and questioning whether a system actually works outside of a demonstration environment.

What You’ll Do

• Design and build applied machine learning and AI systems

• Develop workflows using large language models and other foundation models

• Evaluate model quality, reliability, consistency, and failure modes

• Design benchmarks and experimental frameworks for AI applications

• Build retrieval, ranking, classification, extraction, and synthesis systems

• Develop retrieval-augmented generation and knowledge-based AI workflows

• Explore agentic and multi-step research systems where appropriate

• Build tools that combine structured data, unstructured information, and model-generated outputs

• Develop human-in-the-loop analytical and decision-support workflows

• Compare alternative models, architectures, prompts, retrieval strategies, and evaluation methodologies

• Test systems against adversarial, ambiguous, and out-of-distribution inputs

• Monitor hallucination, uncertainty, and model reliability

• Build reusable research infrastructure and internal analytical tools

• Translate experimental findings into clear recommendations

• Stay current with relevant AI research while separating genuine advances from hype

What We’re Looking For

• Bachelor’s, Master’s, or PhD in computer science, machine learning, statistics, engineering, mathematics, computational science, or a related field

• Strong Python programming skills

• Strong understanding of machine learning fundamentals

• Experience building or evaluating modern AI systems

• Familiarity with LLM APIs, open-source models, or machine-learning frameworks

• Understanding of model evaluation and experimental methodology

• Ability to move quickly from research question to working prototype

• Ability to evaluate systems critically rather than relying on qualitative demonstrations

• Strong technical communication skills

• Curiosity about how humans and machines can make better decisions together

Preferred Qualifications

• Experience with PyTorch, TensorFlow, JAX, or comparable frameworks

• Experience with LLMs, embeddings, vector databases, or retrieval systems

• Experience with RAG architectures

• Familiarity with agentic workflows or multi-stage AI systems

• Experience with model fine-tuning or post-training techniques

• Experience designing automated or human-evaluated benchmarks

• Familiarity with probabilistic modeling, forecasting, or quantitative research

• Experience deploying AI applications in real-world environments

• GitHub projects, research publications, technical writing, or other examples of applied AI work

Apply: Send your resume, GitHub, portfolio, research, or relevant technical work to careers@alphatopiaresearch.com

Employment Type: Full-Time
Function: Risk & Decision Analytics
Location: New York / Remote

The Role

We are looking for a Risk Analytics Associate to analyze complex exposures, develop quantitative frameworks, and support research involving uncertainty and decision-making.

You will work with researchers to translate ambiguous problems into measurable variables, evaluate potential outcomes across scenarios, identify key risk drivers, and communicate the implications clearly.

This is not a traditional reporting-oriented risk role. We are looking for someone interested in understanding why outcomes change and which assumptions matter most.

What You’ll Do

• Develop quantitative frameworks for measuring and understanding risk

• Conduct scenario and sensitivity analysis

• Design stress-testing frameworks

• Identify and quantify major risk drivers

• Analyze nonlinear relationships, dependencies, and tail scenarios

• Develop simulation-based approaches for uncertain outcomes

• Evaluate trade-offs across competing objectives

• Perform risk decomposition and attribution analysis

• Assess model assumptions and limitations

• Compare outcomes across alternative scenarios and methodologies

• Develop decision frameworks under incomplete information

• Build analytical dashboards, research tools, and repeatable workflows

• Translate complex analytical results into concise decision-relevant conclusions

• Collaborate with quantitative researchers and AI researchers on cross-disciplinary projects

• Document assumptions, methodology, uncertainty, and limitations

What We’re Looking For

• Bachelor’s or Master’s degree in mathematics, statistics, economics, finance, engineering, operations research, data science, decision science, or another quantitative discipline

• Strong analytical and structured problem-solving skills

• Strong understanding of probability and statistics

• Comfort working with uncertainty and imperfect information

• Experience with Python, R, SQL, or comparable analytical tools

• Ability to identify the variables that materially drive an outcome

• Strong attention to model assumptions and limitations

• Ability to communicate quantitative findings to both technical and non-technical audiences

• Strong written communication skills

• Intellectual curiosity and disciplined judgment

Preferred Qualifications

• Experience in market risk, portfolio risk, credit risk, model risk, operational risk, insurance, quantitative finance, or decision science

• Experience with Monte Carlo simulation

• Experience with scenario analysis or stress testing

• Familiarity with optimization or probabilistic decision frameworks

• Exposure to financial markets or complex economic systems

• Familiarity with time-series analysis

• Experience building analytical tools or dashboards

Apply: Send your resume and relevant analytical or research work to careers@alphatopiaresearch.com

Employment Type: Internship
Function: Research
Location: New York / Remote

The Role

We are looking for highly curious and quantitatively minded Research Interns to contribute to active research projects across our organization.

Depending on your background and interests, you may work on quantitative modeling, applied AI, data analysis, risk analytics, research infrastructure, or interdisciplinary projects.

You will have the opportunity to work through the full research process: defining a question, collecting evidence, analyzing data, testing hypotheses, documenting findings, and presenting conclusions.

What You’ll Do

• Support active quantitative and analytical research projects

• Collect, clean, organize, and validate datasets

• Conduct exploratory data analysis

• Assist with statistical modeling and hypothesis testing

• Build simple quantitative and machine-learning models

• Perform literature and market research

• Replicate and evaluate published methodologies

• Conduct robustness and sensitivity analysis

• Build research tools and reusable analytical workflows

• Create visualizations and communicate analytical results

• Document methodology, assumptions, and findings

• Present research conclusions to the broader team

• Collaborate with researchers across quantitative research, AI, and risk analytics

What We’re Looking For

• Currently pursuing a Bachelor’s, Master’s, or PhD in a quantitative or analytical discipline

• Strong academic foundation in mathematics, statistics, computer science, economics, engineering, finance, data science, or a related field

• Working knowledge of Python, R, SQL, or another analytical language

• Strong problem-solving ability

• Genuine curiosity about data and complex systems

• Ability to learn unfamiliar subjects quickly

• Strong attention to detail

• Clear written and verbal communication

• Ability to work independently after receiving initial direction

• Willingness to ask questions and challenge assumptions

Preferred Qualifications

• Coursework in probability, statistics, econometrics, machine learning, optimization, or numerical methods

• Prior research experience

• Personal quantitative or AI projects

• Kaggle, GitHub, academic research, publications, or independent projects

• Experience working with large datasets

• Familiarity with financial markets, economics, machine learning, or decision science

Apply: Send your resume, transcript if relevant, and any research, GitHub, portfolio, or project you are proud of to careers@alphatopiaresearch.com