Demonstrator in Advanced Quantitative Methods Job at Birkbeck University of London (London)

Senior Data Scientist

Are you looking for a career move that will put you at the heart of a global fin...

Location

United Kingdom , London

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Hands-on experience in building and deploying Machine Learning solutions in a production environment
Profound knowledge of quantitative methods, probability theory, statistics, and numerical methods
Demonstrated MLOps expertise, encompassing model deployment, versioning, lifecycle management, and proficiency in data drift monitoring and correction
Proven experience in a quantitative field
Exceptional communication, presentation, and interpersonal skills, with a proven ability to influence diverse stakeholders
Master's degree in Data Science, Computer Science, or a related quantitative field
Proficiency in Python and relevant Machine Learning libraries (e.g. scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM, Pandas, NumPy)
Experience with API development, specifically FastAPI, for integrating machine learning models into production systems
Familiarity with MLOps and orchestration tools like MLflow and Apache Airflow

Job Responsibility

Advanced Data Analysis & Modeling: Uncover hidden patterns and develop insights relevant to Credit Risk using advanced statistical, quantitative, and Machine Learning methods
Design and implement robust, scalable machine learning models
Model Optimization & Monitoring: Optimize model performance and design automated solutions for model monitoring, including data drift detection and correction strategies
Explainable AI for Risk: Apply advanced analytics and AI/ML methods to explain root causes for changes in pre-settlement risk, ensuring transparency and interpretability of models
Framework Development: Develop scalable data science frameworks to enable efficient, build-once, deploy-many capabilities for various financial models
Production Integration: Develop and integrate machine learning algorithms into production-grade applications, particularly using FastAPI, ensuring robust, performant, and maintainable solutions
Strategic Product Contribution & Collaboration: Contribute to the full product lifecycle from ideation and requirements gathering to development, launch, and post-launch performance monitoring, partnering with senior leadership, business analysts and engineering teams to gather requirements, manage expectations, and secure alignment
Responsible AI & Governance: Ensure all data products and analytical solutions adhere to Citi's stringent risk, compliance, and regulatory standards, including data privacy and ethical AI principles within the financial domain

What we offer

Generous holiday allowance starting at 27 days plus bank holidays
increasing with tenure
A discretional annual performance related bonus
Private medical insurance packages to suit your personal circumstances
Employee Assistance Program
Pension Plan
Paid Parental Leave
Special discounts for employees, family, and friends
Access to an array of learning and development resources

Fulltime

Principal Epidemiologist

This is an SCS1 grade position at the Medicines and Healthcare products Regulato...

Location

United Kingdom , London

Salary:

81000.00 - 117800.00 GBP / Year

Allen Lane

Expiration Date

Until further notice

Requirements

Doctoral qualification (or equivalent advanced experience) in epidemiology, statistics, or a closely related quantitative discipline
Extensive expertise in the design, implementation, and critical appraisal of advanced epidemiological and statistical methods
Advanced proficiency in programming and computational epidemiology, with expert-level skills in tools such as Python, R, or Stata for handling large, complex, and linked healthcare datasets
Demonstrated leadership in solving complex, strategic challenges, using advanced epidemiological methods, with clear impact on regulatory policy, health system strategy, or major public health initiatives
A strong track record of methodological innovation in epidemiological science
Internationally recognised expertise in at least one of the following domains: Bayesian methods, Causal inference, Dynamic benefit-risk assessment, Genetic and molecular epidemiology, Machine learning and AI, Simulation-based benefit-risk models, Systems epidemiology, Similar advanced and novel methods, Prescription Sequence Symmetry Analysis
Recognised thought leadership, evidenced by publications, invited keynotes, advisory roles, or leadership of expert working groups
Proven ability to shape organisational culture and strategic direction
Extensive experience communicating complex technical and conceptual material with clarity and influence
A sustained record of high-impact scientific publication

Job Responsibility

Lead the development and implementation of advanced epidemiological methods to transform how the MHRA identifies, evaluates, and mitigates risks associated with medicines and medical devices
Deliver high-impact, cross-cutting initiatives that have the potential to shape the Agency’s future capabilities
Pioneer innovative approaches that strengthen the UK’s regulatory science framework by harnessing real-world data
Act as a thought leader and methodological innovator – driving forward high-profile projects, advising senior leadership, and contributing to the MHRA’s standing as a global leader in regulatory epidemiology
Build and maintain strategic partnerships with academic institutions, healthcare organisations, regulators and international bodies
Represent the MHRA externally in national and international committees, expert working groups, and collaborative initiatives
Work collaboratively with team members and colleagues across the Agency to achieve shared objectives and maximise the impact of their work

What we offer

Eligibility to the Civil Service pension scheme (employer contribution of 28.97%)
Flexible working

Fulltime

RDSO Sr. Mgr Data Sciences

Data is the new gold. Digitalization is generating large quantities of data and,...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Any degree and 12 -17 years of experience in statistics, data science, operations research, mathematics, econometrics, business administration, or a related quantitative field
12-17 years of experience delivering complex analytical projects using quantitative methods, multivariate statistics, predictive modeling, and advanced analytics techniques
Demonstrated experience building, deploying, and optimizing machine learning models to drive business outcomes
Experience leading offshore or globally distributed analytics teams, preferably within an India delivery model
Strong ability to translate business requirements into analytical plans and influence decision-making through clear communication
Hands-on experience with modern data platforms and cloud technologies (e.g., AWS, Snowflake, Spark, Databricks)
Proficiency in Python, R, Scala, Java, SQL, and BI tools (e.g., Tableau, Spotfire)
Demonstrated application of advanced analytics, AI/ML, NLP, and statistical modeling to complex business problems
Strong written, verbal, and presentation skills with senior leadership audiences
Experience operating effectively in a matrixed, global environment

Job Responsibility

Design and develop analyses (e.g., descriptive, diagnostic, predictive, prescriptive) to enable concrete insights and inform timely decision-making
Strategize with partners across the organization to build scalable, production-grade AI/ML products and apply consistent approaches to solving complex business problems
Identify key business questions required to meet evolving needs
prioritize resources to address critical business issues and decisions
Design and build analytical frameworks, tune model parameters, and monitor model performance over time
Lead and provide thought leadership across end-to-end development, deployment, and sustainment of digital and analytics solutions
Partner with IS and data engineering teams to define data requirements, automate model retraining, and ensure robust deployment pipelines
Ensure dashboards and downstream products are fed by reliable, high-quality analytical models aligned to business needs
Apply agile delivery methods to ensure efficient, integrated, and scalable business and system processes
Build, lead, and develop a high-performing India-based Data Sciences team, including hiring, onboarding, performance management, coaching, and career development

What we offer

Full support and career-development resources to expand your skills and maximize your potential
A diverse and inclusive community of belonging, where teammates are empowered to contribute and lead
Competitive total rewards package supporting health, wealth, work/life balance, and career growth

Fulltime

Data Scientist

High-performing, high-impact tactical and strategic position requiring outstandi...

Location

United States , Novato

Salary:

51.00 - 75.00 USD / Hour

BioMarin Pharmaceutical

Expiration Date

Until further notice

Requirements

Master’s (minimum) or PhD (strongly preferred) in a quantitative discipline (data science or closely related field)
5+ years of work experience in data analysis
Quantitative skills
Expertise with hands-on data analysis including programming (SAS, R, Python, SQL, etc.)
Demonstrated knowledge of core statistical and data science concepts and principles
Basic familiarity with statistical methods common in clinical research such as linear models, multivariate analysis, longitudinal data analysis, categorical data analysis, and study design
Applied experience with a variety of machine learning and data mining techniques (linear models, clustering, decision trees, random forests, boosting, neural networks, text mining, scenario analysis, simulation, etc.) including understanding of their real-world advantages and drawbacks
Ability to manipulate and make best use of complex, messy data sets
Mastery of effective presentation of data, particularly data visualization
Aptitude to learn new quantitative methods

Job Responsibility

Work with unique, complex, messy data sets
Solve difficult, unusual analysis problems, applying advanced analytical methods as needed
Exhibit solid understanding of core statistical concepts and advanced methods while at the same time favoring simplicity and exhibiting flexibility in how to approach data
Carry out hands-on the full process of conducting analyses: conceptualization and planning, data gathering, statistical analysis, interpretation of results, and reporting and presentation. Supervise teams to do the same
Design and plan data collection and analysis to answer business questions
Interact effectively with cross-functional counterparts: understand their problems, formulate practical, actionable approaches, and communicate the solutions effectively
Exhibit exceptional communication skills including report-writing and presentation
Educate counterparts with widely varying functional roles and technical backgrounds on concepts of data science to equip them to effectively utilize their own data

What we offer

discretionary annual bonus
discretionary stock-based long-term incentives
paid time off
company-sponsored medical, dental, vision, and life insurance plans

Fulltime

Quantitative Analyst, Vice President

Part of Markets Quantitative Analysis, the Equity Quantitative Derivative Team i...

Location

United Kingdom , London

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Demonstrated years of experience in a comparable quantitative modelling or analytics role, preferably in the financial sector
Expert-level C++ development, including contribution to large-scale library design and development
Experience with scripting languages and/or implementation of payoff scripting frameworks
Expert-level experience in derivatives pricing and product knowledge, ideally in equity exotics
Deep knowledge of numerical methods, particularly Monte Carlo simulation and PDE solvers
Advanced degree in Quantitative Finance, Mathematics, Physics, or related field
Excellent communication and collaboration skills
Consistently demonstrates clear and concise written and verbal communication skills

Job Responsibility

Develop analytics libraries used for pricing and risk management
Design, build, and enhance a pricing library for derivative products and ensure robust model integration
Implement and maintain derivative pricing models (e.g. stochastic/local volatility, stochastic correlation, jump), using numerical techniques for valuation including Monte Carlo methods and partial differential equation solvers
Optimise the core codebase to ensure performance, stability, and engineering excellence
Develop and support product payoff scripting frameworks for flexible trade representation
Establish best practices for testing, validation, and model governance
Collaborate closely with Traders, Structurers, and technology professionals
Work in close partnership with control functions such as Legal, Compliance, Market and Credit Risk, Audit, Finance in order to ensure appropriate governance and control infrastructure
Build a culture of responsible finance, good governance and supervision, expense discipline and ethics
Appropriately assess risk/reward of transactions when making business decisions

What we offer

Work in a challenging area of the financial industry with one of the world's leading companies with exposure to variety of products, processes and controls
Cooperation with a high quality, international, multicultural and global team
Work in a friendly and diversified environment, appreciating differences in style and perspective and using them to add value to decisions leading to organizational success
Management supporting balanced and agile work (flexible working hours, home office)
A chance to make a difference with various affinity networks and charity initiatives
Generous holiday allowance starting at 27 days plus bank holidays
increasing with tenure
A discretional annual performance related bonus
Private medical insurance packages to suit your personal circumstances
Employee Assistance Programme

Fulltime

Senior Director, Enterprise Stakeholder Engagement

The Senior Director of Enterprise Stakeholder Engagement will lead PepsiCo’s ent...

Location

United States , Purchase, New York; Washington, District of Columbia

Salary:

157200.00 - 312000.00 USD / Year

Pepsico

Expiration Date

Until further notice

Requirements

10+ years of experience in public policy, government affairs, regulatory affairs, external relations, risk management, or a related field
Proficiency with statistical tools and data platforms (e.g., advanced Excel modeling, R, Python, SQL, or similar analytics software)
Strong quantitative, analytical, and statistical capabilities, with demonstrated experience applying data-driven methods to assess and model organizational risk
Demonstrated experience operating in politically sensitive or high-risk external environments
Strong judgment and ability to assess ambiguous or complex stakeholder dynamics
Experience advising and influencing senior executives
Proven ability to work cross-functionally and navigate complex, matrixed organizational structures

Job Responsibility

Own and evolve PepsiCo’s enterprise stakeholder engagement framework, including stakeholder mapping, prioritization, and governance processes
Maintain a centralized, enterprise-wide view of external stakeholders to enable visibility, coordination, and strategic alignment
Apply consistent, enterprise-wide criteria to assess stakeholder relevance, influence, risk exposure, and strategic alignment
Ensure stakeholder engagement and funding decisions reflect enterprise priorities and reinforce PepsiCo’s broader external strategy
Lead structured review and alignment processes for enterprise-level stakeholder engagement decisions, ensuring transparency, consistency, and accountability
Design dashboards, models, and decision support systems that inform enterprise strategy and stakeholder management
Conduct quantitative risk assessment, probability modeling, scenario analysis, forecasting, and development of risk metrics, indices, and scoring frameworks that translate uncertainty into actionable insights
Integrate quantitative findings into governance and stakeholder engagement strategies, linking risk exposure to operational, reputational, regulatory, and social impact considerations
Use data-driven methodologies to help the enterprise anticipate emerging stakeholder trends, external pressures, and evolving expectations
Serve as a trusted advisor to senior leaders on external stakeholder engagement strategy

What we offer

Bonus based on performance and eligibility target payout is 35% of annual salary paid out annually and an additional target payout of 15% of annual salary is paid out over 3 years following the end of the performance period
Long term incentive equity may be awarded based on eligibility and performance
Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement
Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan
Car allowance

Fulltime

Investment Data Scientist

As part of the AMS Research team, the Investment Data Scientist plays a key role...

Location

United States , Saint Petersburg

Salary:

Not provided

Raymond James

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, Economics, Finance, or a related quantitative field
3–6 years of hands-on experience with Python development and quantitative analysis
Demonstrated experience building optimization models, statistical systems, and/or automated workflows
Python libraries for data manipulation and array mathematics: pandas, NumPy, SciPy, and optimization libraries such as CVXPY
Statistical modeling and optimization: mixed integer programming, regressions, time series, and Monte Carlo simulation
Data visualization: Streamlit, Tableau, Power BI, Plotly Dash, or similar platforms
Quantitative finance: portfolio construction methods, risk modeling, and financial data analysis
Writing clean, documented, and version-controlled Python code
Translating business problems into quantitative models and technical solutions
Building and maintaining automated workflows

Job Responsibility

Develop and maintain robust Python code for portfolio construction, statistical analysis, and automation of investment workflows
Design and implement portfolio optimization algorithms
Apply advanced statistical methods to extract insights from financial datasets
Collaborate with Investment Committee members, analysts, and quant team members to align model development with investment objectives and operational needs
Build automated processes to eliminate manual tasks, reduce errors, and improve workflow efficiency
Create interactive dashboards and visualizations to communicate analytical findings

Fulltime

Manager, Data Science

Intuit is the global financial technology platform that powers prosperity for th...

Location

Canada , Toronto

Salary:

168000.00 - 227500.00 USD / Year

Intuit

Expiration Date

Until further notice

Requirements

7+ years of experience applying data science, advanced analytics, or quantitative methods to marketing, growth, or lifecycle use cases
Experience leading and developing teams of data analysts or data scientists, with a demonstrated ability to coach both technical and business skills
Strong expertise in statistics, experimental design, and causal inference, including A/B testing, multivariate testing, and incremental lift measurement
Hands-on experience building or operationalizing machine learning models (e.g., propensity, segmentation, churn, personalization) in partnership with engineering or platform teams
Proficiency with SQL and Python (or equivalent) for data analysis, experimentation, and modeling
Proven ability to lead cross-functional analytical projects end-to-end, from problem framing through execution and executive readout
Strong data storytelling and influence skills, with experience presenting insights and recommendations to senior leaders
Domain experience in lifecycle marketing, CRM, fintech, SaaS, or marketing technology preferred

Job Responsibility

Lead a team of marketing data scientists in defining and executing end-to-end data science roadmaps that support lifecycle marketing across QuickBooks Services (Capital, Payroll, Payments, Bill Pay) and Mailchimp, aligned to short- and long-term business outcomes
Own the measurement, experimentation, and modeling strategy for lifecycle marketing initiatives, including onboarding, attach, upsell, retention, and active use, leveraging causal inference, experimentation frameworks, and advanced analytics
Design, evaluate, and scale incrementality measurement approaches, including randomized experiments, holdouts, and quasi-experimental methods, to quantify the true impact of lifecycle marketing across Email, IPD, Push, SMS, Web, and cross-channel programs
Drive development and adoption of machine learning models for lifecycle marketing use cases such as propensity scoring, churn risk, personalization, and next-best-action, in partnership with central DS and ML platform teams
Translate complex analytical findings into clear, data-backed perspectives on marketing and business performance, with actionable recommendations tied to customer growth, revenue, and retention
Partner closely with Lifecycle Marketing, CRM Analytics, Product, GTM, and Finance to ensure strong metric definitions, data quality, and alignment between marketing performance and financial outcomes
Shape forward-looking data science capabilities by identifying gaps in experimentation, modeling, and data infrastructure, and influencing investments that improve learning velocity and decision-making
Manage a team of data scientists and contractors, including coaching on technical rigor, experimental design, modeling best practices, and data storytelling, while owning prioritization, intake, and delivery

Fulltime

Select Country

Demonstrator in Advanced Quantitative Methods

Job Description

Job Responsibility

Requirements

Looking for more opportunities?