Modeler Job at Disney (London)

Senior Analyst and statistical modeler

Part of the cornerstone of our firm’s marketing and analysis efforts.

Location

United States , Tempe

Salary:

Not provided

Zion & Zion

Expiration Date

Until further notice

Requirements

Extremely well versed in statistics
Masters in Statistics or Applied Mathematics or similar
Expert in creation of regression models, time series models and other modeling techniques
Significant and up-to-date knowledge in statistical modeling
Background in programming
Business savvy
Exceptional written and oral communications skills
Understanding of concepts like revenue, margins, return on investment
Experience in web analytics is desirable

Job Responsibility

Taking inputs such as web traffic data, schedules for TV and radio spots, marketing spend, revenue generated, etc. and building models to assess what effect the independent variables had on the dependent variables
Applying the right math and algorithms to remove seasonal and other trends from parts of the data
Using directional indicators without statistical significance to make recommendations based on models and data
Presenting to clients

Avp ml and genai model validation

Embark on a transformative journey as an AVP ML and GenAI Model Validation at Ba...

Location

India , Noida

Salary:

Not provided

Barclays

Expiration Date

Until further notice

Requirements

Highly numerate, evidenced by an Honours degree, master’s, or PhD (or equivalent) in a quantitative discipline such as Computer Science, Mathematics, Physics, Operational Research, Economics, Engineering, or Finance
Experience developing, validating, or independently reviewing best‑in‑class tools and AI/ML models for large financial institutions or comparable regulated environments, with the ability to effectively challenge and improve model methodologies and model management processes
Strong analytical and technical expertise in AI/ML modelling, including experience with ML algorithms (e.g., XGBoost, LightGBM, Random Forest), NLP models, and deep learning frameworks (e.g., TensorFlow, PyTorch, Keras)
Experience developing or validating AI/ML models on large datasets in Hadoop/AWS environments
Designed, fine‑tuned, and shipped Generative AI models - transformer‑based LLMs, RAG systems for grounded retrieval, and GANs-using PyTorch/TensorFlow and Hugging Face, including prompt engineering, RLHF, and rigorous evaluation of GenAI models
Hands‑on experience with Generative AI technologies, including Large Language Models, Transformers, retrieval‑augmented generation (RAG), and prompt‑based systems
familiarity with LangChain and LangGraph
Experience designing, developing, validating, or reviewing agent‑based AI architectures, including multi‑agent orchestration, task planning, memory management, and safeguard mechanisms
Sound understanding of financial services regulatory expectations and model risk guidance (e.g., SR 11‑7, SS1/23, IFRS 9, EU AI Act etc.)
Strong communication and influencing skills, with the ability to produce high‑quality written material for both technical and senior non‑technical audiences

Job Responsibility

Validation of models for their intended use and scope, commensurate with the complexity and materiality of the models
Approval or rejection of a model or usage based on assessment of the model’s conceptual soundness, performance under intended use and the clarity of the documentation of the model’s inherent risks, limitations and weaknesses
Assessment of any compensating controls used to mitigate Model risk
Documentation of validation findings and recommendations in clear and concise reports, providing actionable insights for model improvement
Evaluation of the coherence of model interactions and quality of Large Model Framework aggregate results that generate output for regulatory submissions or management decision making and planning
Design of the framework and methodology to measure and, where possible, quantify model risk, including the assessment of framework level uncertainty

What we offer

Hybrid working
Modern workspaces, collaborative areas, and state-of-the-art meeting rooms
Facilities include wellness rooms, on-site cafeterias, fitness centers, and tech-equipped workstations

Fulltime

Regulatory Model Monitoring Analyst

This position within US Personal Banking and Wealth Management will focus on reg...

Location

India , Bengaluru

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Advanced Degree (Masters required, PhD preferred) in Statistics, Applied Mathematics, Operations Research, Economics, MBA (Finance), or other highly quantitative discipline
2+ years’ experience in performing quantitative analysis, statistical modeling, loss forecasting, loan loss reserve modeling, and particularly econometric modeling of consumer credit risk stress losses
Experience with dynamics of unsecured products a strong plus
Active role in performing some analytical components of an econometric modeling-driven stress loss process (data collection, data integrity QA/QC/reconcilements, pre-processing, segmentation, variable transformation, variable selection, econometric model estimation, sensitivity testing, back testing, out-of-time testing, model documentation, and model production implementation)
Exposure to various stress loss modeling approaches at the segment or account level preferred
Able to communicate technical information verbally and in writing to both technical and non-technical audiences
Proficiency in SAS/SQL/Oracle/Unix/Microsoft Word, Excel and PowerPoint
Work as an individual contributor

Job Responsibility

Analyze quarterly model performance results and other required model performance analysis for production models
When forecast or performance shifts are observed, perform diagnostic analytics around drivers including standard reporting as well as drill down analytics
Explain model results and review drivers of observed gaps or deterioration in model performance with regional/country risk managers and internal model development teams
Perform formal quarterly and annual model review according to MRM’s guidance and standards
Respond to MRM’s questions as needed
Obtain and conduct QA/QC on all data required for CCAR/CECL model development
Deliver comprehensive model documentation
Work closely with cross functional teams, including country/region’s business stakeholders, model validation, governance teams, model development and implementation teams

Fulltime

Model Monitoring, Analytics & Insights – Vice President

This position focuses on model performance monitoring, analytics, and insights f...

Location

India , Bengaluru

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Advanced Degree (Bachelors required or Masters preferred) in Statistics, Computer Science, Operations Research, Economics
Strong programming (SAS, SQL, Python, etc.) skills
Understanding of traditional modeling processes (linear/ logistic regression, segmentation, decision tree) and machine learning algorithms (Random Forest, Gradient Boosting, XG Boost, SVM, etc.), time series, linear/nonlinear optimization
Strong understanding of relevant model metrics / KPIs & bring out insights on model performance tracking
Good communication skill to be able to articulate technical information verbally and in writing to both technical and non-technical audiences is a must
Extensive experience in model monitoring/validation, performance scorecards, etc. in Excel, Tableau, Cognos, etc.
Experience in developing optimal/ automated solution of reporting processes using SAS, Excel VBA, Tableau will be a plus
10+ Years of relevant experience in model analytics and insights
At least 7 years of extensive experience in model monitoring, generating business insights, analytical projects contributing business value
Experience in automating reporting processes would be a plus

Job Responsibility

Perform Root Cause Analysis explaining model performance to second line of defense and Policy teams for Business risk decisioning
Analyze & bring out Insights for Credit Risk Non-Regulatory Scoring/ Non-Scoring Segmentation models including performance assessment, drill down root cause analysis for performance deterioration, coming up with mitigation action providing rational for continued usage of the model without business impact
Present model performance to senior stakeholders, CROs, Risk Policy managers, Sponsors explaining the heath of the model, connecting model metrices to business scenarios explaining the breach in model performance
Explain model performance to second line (Model Risk Management) of defense providing rational of model performance deterioration (if any), explaining the applicability of the usage of the model
Respond to queries from 3rd Line of Defense (Internal and External Auditors) on model performance
Work effectively across cross functional teams - Development, Implementation, Policy, Validation and Governance teams - coordinating the horizontal model usage and maintenance activities
Perform analysis for benchmark models and other ad hoc analysis as required by business/validation teams
Develop knowledge and drive discussions on Model usage across channels, score range with Risk Strategy managers
Conduct QA/QC on all steps (e.g., input data, model output, etc.) required for model monitoring and production forecast reporting
Deliver comprehensive write-up of ongoing model performance assessment, Annual Model Review / Revalidation documents

What we offer

Global benefits supporting employee well-being, growth, and work-life balance

Fulltime

Balance Sheet Management Modeling – AVP

The Balance Sheet Management Sr. Analyst is a seasoned professional role respons...

Location

India , Mumbai

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

6-8 years of relevant statistical modeling /econometrics experience in financial domain
PG / Masters / PhD in quantitative discipline such as Statistics, Economics, Mathematics, or related discipline is preferred
Experience in developing econometric models and deep understanding of statistical techniques such as Linear Regression, Logistic Regression, Time Series, Panel Regression, Error Correction Models, Seemingly Unrelated regression and Cointegration and Machine Learning Techniques
Working experience with Artificial Intelligence/Machine Learning techniques and packages (ChatGPT, Copilot)
Hands-on experience in programming and modeling using Python and related packages (GitHub, DataFlame) is must
Experience with SQL and databases
Domain knowledge and experience in PPNR, Fixed Income Securities, Mortgage Modeling, Deposit Modeling, Asset Liability Management, Interest Rate Risk, Capital Planning
Broad understanding of financial products, accounting principles, investment, accrual products and corporate finance concepts
Excellent presentation skills
Ability to build key cross functional and cross business relationships

Job Responsibility

End-to-end development and governance and support of models in treasury/IRRBB space
End-to-End model development includes econometric forecasting models for key Balance sheet and income statement line items for capital and business planning purposes
Calculation of Net Interest Income (NII), Non-Interest Revenue (NIR), Interest Rate Exposure (IRE), Economic Value Sensitivity (EVS), and other associated interest rate risk metrics
Model governance and support includes reviewing and timely submission of model documentations such as Model development document (MDDs), Annual Model Review (AMRs), Ongoing Performance Assessment (OPAs), Model Change Addendum (MCAs), Limitation Record Change (LRCs) to Model Risk Management
Develop and maintain a comprehensive modeling system that maintains consistent approach to data quality and modeling methods, audit, back test, tracking, annual validation
Present technical matters in a way that is meaningful to the audience and align with Model Risk Management on modeling and validation practices
Build key relationships with finance and business teams
Create a culture of accountability and strict quality control of the data integrity and modeling processes

Fulltime

Non-Traded Models IVU-VP

Embark on a transformative journey as a Non-Traded Models IVU-VP at Barclays, wh...

Location

India , Noida; Mumbai

Salary:

Not provided

Barclays

Expiration Date

Until further notice

Requirements

Validate credit risk related regulatory (IRB, IFRS9, CCAR and Stress Testing) models for wholesale portfolios by following Bank’s policies and standards
Perform technical analysis and/or build alternative benchmarks to new and existing models, in line with the requirements set out in the bank’s standards and policies
Work as an Individual Contributor and also Mentor a team of 2-3 analysts
Review regulatory requirements to ensure compliance with different regulatory guidelines e.g. SR 11-7, PRA, FRB, SS-1/23
Support the development and review conformance with appropriate policies including Group Model Risk policy
Solid understanding of the quantitative techniques used in developing and validating models including credit risk related regulatory (IRB, IFRS9, CCAR, Stress-testing, PD, EAD, LGD) models for wholesale portfolios
Hands-on experience in the use of statistical packages such as Python, SAS, R
Expert user of Microsoft Excel and other Microsoft Office tools
An ability to identify and analyse appropriate external data sources including macro-economic variables for model development or validation along with excellent communication and stakeholder management skills

Job Responsibility

Validation of models for their intended use and scope, commensurate with the complexity and materiality of the models
Approval or rejection of a model or usage based on assessment of the model’s conceptual soundness, performance under intended use and the clarity of the documentation of the model’s inherent risks, limitations and weaknesses
Assessment of any compensating controls used to mitigate Model risk
Documentation of validation findings and recommendations in clear and concise reports, providing actionable insights for model improvement
Evaluation of the coherence of model interactions and quality of Large Model Framework aggregate results that generate output for regulatory submissions or management decision making and planning
Design of the framework and methodology to measure and, where possible, quantify model risk, including the assessment of framework level uncertainty

What we offer

modern workspaces
collaborative areas
state-of-the-art meeting rooms
wellness rooms
on-site cafeterias
fitness centers
tech-equipped workstations
flexible working arrangements
hybrid working

Fulltime

Data Modeller

Join us as a Data Modeller at Barclays, where you'll spearhead the evolution of ...

Location

India , Pune

Salary:

Not provided

Barclays

Expiration Date

Until further notice

Requirements

Partner with business stakeholders to understand their data needs and their desired functionality for the data product. Translate these requirements into clear data modelling specifications
Designs and implements high-quality data models that optimize data access, storage, and analysis as well as ensuring alignment to BCDM
Creates comprehensive and well-maintained documentation of the data models, including entity relationship diagrams, data dictionaries, and usage guidelines
Collaborates with data engineers to test and validate the data models
Obtains sign-off from the DPL, DPA and the Technical Product Lead on the logical and physical data models
Continuously monitor and optimise the performance of the models and data solutions to ensure efficient data retrieval & processing
Collaborates with data engineers to translate into physical data models and throughout the development lifecycle
Manages the business as usual ‘BAU’ data model and solution covering enhancements and changes
Helps DSA in defining the legacy estate migration and decommissioning roadmap for the assigned BUK data domain
You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills

Job Responsibility

Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification, documenting data sources, methodologies, and quality findings with recommendations for improvement
Designing and building data pipelines to automate data movement and processing
Apply advanced analytical techniques to large datasets to uncover trends and correlations, develop validated logical data models, and translate insights into actionable business recommendations that drive operational and process improvements, leveraging machine learning/AI
Through data-driven analysis, translate analytical findings into actionable business recommendations, identifying opportunities for operational and process improvements
Design and create interactive dashboards and visual reports using applicable tools and automate reporting processes for regular and ad-hoc stakeholder needs
To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions
Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others
OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes
Consult on complex issues

What we offer

Hybrid working
We’re committed to providing a supportive and inclusive culture and environment for you to work in
We celebrate the unique perspectives and experiences each individual brings, believing our differences make us stronger and drive success

Fulltime

Balance Sheet Management Modeling - VP

The Balance Sheet Management Sr. Analyst is a seasoned professional role respons...

Location

India , Mumbai

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

8+ years of relevant statistical modeling/econometrics experience in financial domain
PG/Masters/PhD in quantitative discipline such as Statistics, Economics, Mathematics, or related discipline is preferred
Certifications such as FRM, CFA is a plus
Experience in developing econometric models and deep understanding of statistical techniques such as Linear Regression, Logistic Regression, Time Series, Panel Regression, Error Correction Models, Seemingly Unrelated Regression and Cointegration and Machine Learning Techniques
Working experience with Artificial Intelligence/Machine Learning techniques and packages
Hands-on experience in programming and modeling using Python and related packages
Working knowledge of statistical packages like SAS/R is a plus
Experience with SQL and databases
Experience in Excel VBA is a plus
Domain knowledge and experience in PPNR, Fixed Income Securities, Mortgage Modeling, Deposit Modeling, Asset Liability Management, Interest Rate Risk, Capital Planning

Job Responsibility

End-to-end development and governance and support of models in treasury/IRRBB space
End-to-End model development including econometric forecasting models for key Balance sheet and income statement line items for capital and business planning purposes such as Net Interest Income, Non-Interest Revenue, Interest Rate Exposure, Economic Value Sensitivity, and others
Applies analytical thinking and knowledge of statistics/modeling/data analysis tools and methodologies
Reviewing and timely submission of model documentations to Model Risk Management and other stakeholders
Develop and maintain a comprehensive modeling system ensuring consistent approach to data quality and modeling methods, audit, back test, tracking, annual validation
Present technical matters meaningfully to align with Model Risk Management on modeling and validation practices
Build key relationships with finance and business teams
Create a culture of accountability and strict quality control of the data integrity and modeling processes

Fulltime

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