Quantitative researcher to help build out a systematic macro (futures, FX, and vol) strategies.
Compensation
The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package.
Responsibilities
Develop systematic trading models across FX, commodities, fixed income, and equity markets
Alpha idea generation, backtesting, and implementation
Assist in building, maintenance, and continual improvement of production and trading environments
Evaluate new datasets for alpha potential
Improve existing strategies and portfolio optimization
Requirements
Masters or PhD in mathematics, statistics, physics or other quantitative discipline. PhD in statistics or machine learning is a plus
Nice to have: PhD in statistics or machine learning
Conduct research within the Nuclear Theory Group, developing and applying microscopic transport models and AI/ML methods to study dense nuclear matter using heavy-ion collision data.
Responsibilities
Develop and improve microscopic transport approaches, particularly the SMASH transport model
Apply advanced computational and statistical methods, including Bayesian inference and AI/ML
Mentor graduate and undergraduate students
Disseminate results through publications, conferences, and workshops
Requirements
PhD in Nuclear Physics or related field
Nice to have: SMASH transport model experience
Nice to have: knowledge of dense nuclear matter physics
Nice to have: experience with Bayesian parameter estimation
Nice to have: experience with machine learning methods in scientific data analysis
Senior Scientist role focused on AI for Oncology Clinical Development, combining machine learning expertise with computational science to transform drug discovery and clinical study design.
Compensation
The annual base pay for this position ranges from $124,713.60 - $187,070.40 annually.
Responsibilities
Lead the technical delivery of complex, high-stakes AI initiatives.
Evaluate and develop advanced AI methods across problem definition, data strategy, governance, algorithm development, validation, and adoption.
Create and validate novel AI solutions for clinical study design, execution, strategy, and decision-making.
Apply data, models, and insights across cancer biology and multiple drug modalities.
Collaborate across key Oncology areas, including hematology, cell therapy, antibody-drug conjugates, small molecules, and biologics.
Requirements
PhD in a quantitative discipline such as computer science, mathematics, physics, biophysics, bioinformatics, computational biology, computational neuroscience, or biostatistics
Nice to have: Biology or biomedical research
Nice to have: Machine learning for molecular data (DNA, RNA, proteins)
Nice to have: Imaging data (radiology, microscopy)
Nice to have: Clinical text, electronic health records, clinical notes
Develops and implements HEOR Analytics strategy, designs and executes real‑world evidence studies, manages analytics consultants, and provides statistical guidance to support value decisions for therapeutic areas.
Responsibilities
Designs and implements HEOR studies that support clinical, economic, and patient centered value propositions
Manages analytics consultants and oversees analysis activities
Provides statistical guidance or methodology and interprets analysis results
Serves as a real‑world data expert, identifies data sources, and provides strategies to generate valid evidence
Provides new insights for disease area to shape clinical development strategies
Requirements
BS/MS/MA in Statistics, Biostatistics, Computer Science, Mathematics
Senior Scientist role focused on AI for Oncology Clinical Development, combining machine learning expertise with scientific research to transform drug development.
Compensation
The annual base pay for this position ranges from $124,713.60 - $187,070.40 annually.
Responsibilities
Lead the technical delivery of complex, high-stakes AI initiatives.
Evaluate and develop advanced AI methods across problem definition, data strategy, governance, algorithm development, validation, and adoption.
Create and validate novel AI solutions for clinical study design, execution, strategy, and decision-making.
Apply data, models, and insights across cancer biology and multiple drug modalities.
Collaborate across key Oncology areas, including hematology, cell therapy, antibody-drug conjugates, small molecules, and biologics.
Requirements
PhD in a quantitative discipline such as computer science, mathematics, physics, biophysics, bioinformatics, computational biology, computational neuroscience, or biostatistics
Lead and manage global health economics and outcomes research analytics initiatives, developing strategy, overseeing studies, and providing statistical guidance to support value decisions for Alexion products.
Responsibilities
Designs and implements HEOR studies that support the clinical, economic, and patient centered value propositions, as well as reimbursement requirements for the therapeutic areas of interest.
Manages analytics consultants and oversees the analysis activities by providing inputs to the analysis plans, monitoring the study conduct and reviewing study results.
Provides statistical guidance or methodology and interprets the analysis results.
Serves as a real-world data expert, identify data sources, and provide strategies to generate valid evidence from the appropriate databases.
Provide new insights for disease area to help shape clinical development strategies and generates real world evidence for value decisions of therapies.
Requirements
BS/MS/MA in Statistics, Biostatistics, Computer Science, Mathematics and/or PhD in related area
Lead the design, development, and deployment of advanced media measurement and marketing effectiveness models to drive data‑driven decision‑making for clients.
Responsibilities
Lead end‑to‑end development and delivery of Marketing Mix Models (MMM) using open‑source frameworks
Manage, mentor, and guide a team of data scientists
Collaborate with senior client stakeholders and cross‑functional teams
Design Bayesian and frequentist MMM frameworks
Oversee model validation, diagnostics, and testing
As a Marketing Mix Modeling (MMM) Manager, you will lead the design, development, and deployment of advanced media measurement and marketing effectiveness models to drive data-driven decision-making for clients.
Locations (2)
Kolkata, West Bengal, India
India
Responsibilities
Lead end-to-end development and delivery of Marketing Mix Models (MMM) using open-source frameworks including PyMC, Meridian, and Robyn.
Manage, mentor, and guide a team of data scientists, setting clear objectives and ensuring high-quality model outputs.
Collaborate with senior client stakeholders and cross-functional teams to translate business objectives into robust measurement strategies.
Design Bayesian and frequentist MMM frameworks to evaluate media spend effectiveness, attribution, and budget optimization across channels.
Oversee model validation, diagnostics, and testing to ensure reliability and business relevance of insights.
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