Data Scientist

<!–

Description

–>

IFC a member of the World Bank Group is the largest global development institution focused on the private sector in emerging markets. We work in more than 100 countries, using our capital, expertise, and influence to create markets and opportunities. Our mission is to leverage the power of the private sector to end extreme poverty and boost shared prosperity on a livable planet.

Information technology is an integral part of the strategic initiatives for all the core business functions at IFC. Within Corporate Information and Technologies (CIT), Data Engineering, AI and Platforms (CITDE) organization provides comprehensive data and analytics support for IFC’s various organizations, such as Economics & Private Sector Developments, Global Industries, Climate Business, Treasury and Mobilization, any many more. A robust engagement model with business ensures prioritization of the business requirements & focus on delivery. The solution landscape encompasses a wide variety of in-house and customized data applications, AI/ML solutions and scaled capabilities which meet the business needs of IFC departments.

Data Engineering & Platforms (CITDE) organization is seeking a Data Scientist responsible for leading our machine learning and artificial intelligence deliverables & strategy, and the execution of related programs and practices that drive measurable business outcomes. This role is pivotal to drive value for business stakeholders across International Finance Corporation’s (IFC) various organizations. This role involves establishing, leading, and operating the Machine Learning (ML) and Artificial Intelligence (AI) function to deliver scalable solutions and products while managing data as a valued asset.

Duties and Responsibilities:

• Implement AI-driven analytics solutions to uncover deeper insights, predict trends, and support data-driven decision-making across the enterprise. 
• Institute an enterprise operating model for data and AI that is consistent with the capabilities and competencies required to execute the strategy. 
• Champion the use of Artificial Intelligence (AI), Large Language Models (LLM), and Natural Language Processing (NLP) technologies to enhance business processes and customer engagement. 
• Supports and helps build a generative AI practice within AI & Data. This includes supporting use case development and associated stakeholder management in various business areas. It also means influencing infrastructure and tooling (in collaboration with IT Ops, etc.), education of stakeholders and community, and governance (in collaboration with model governance team, legal, and risk). 
• Independently leads and contributes to data analysis and modeling projects from project/sample design, business review meetings with internal and external clients deriving requirements/deliverables, reception and processing of data, performing analyses and modeling to final reports/presentations, communication of results and implementation support. 
• Utilizes advanced statistical/AI techniques to create high-performing predictive models and other solutions to address business objectives and client needs. Tests new statistical and machine learning methods, software and data sources for continual improvement of quantitative solutions. 
• In-depth knowledge in SQL query techniques and data mining to explore a variety of data sources, gain data expertise, perform summary analyses and prepare modeling datasets. Deploys analytical solution in production systems. 
• Works closely with the business stakeholders, technology solutions team, Risk, and several other groups in designing, building, and implementing ML models and AL solutions. 
• Evangelizes the use of AI-powered data-based decision making and Analytics within International Finance Corporation (IFC). 
• Proactively and effectively communicates in various verbal and written formats with internal stakeholders on product design, data specification, and ML model implementations. Resolves problems and removes obstacles to timely and high-quality project completion.

Selection Criteria:

• Master’s degree in a quantitative discipline such as statistics, computer science, mathematics, economics, or any related field. 
• 5+ years of experience with predictive analytics using large and complex datasets. 
• In-depth expertise in both parametric statistical modeling techniques (linear regression, GLM, survival analysis, time series, etc.) and non-parametric techniques (GBM, NN, NLP). 
• Experience in techniques addressing overfitting (Ridge, Lasso, elastic nets), variable selection techniques, feature creation (transformation, binning, high level categorical reduction, etc.), validation (holdouts, CV, bootstrap) and model performance measures.
• Prior programming experience in languages such as R, Python, SPARK, SQL. Comfort with professional software development process and GitHub. 
• 5+ years of experience in deploying real-time models into production environments. This includes production-ready code, containerizing models, testing, and integration into business processes. 
• Detailed recent NLP experience (basic techniques, large language models, transformers, etc.) 
• 2+ years of experience with generative AI solutions (both development and deployment/integration). Ideally this would include training, fine-tuning and prompt engineering. 
• Experience with disparate impact testing vs. protected classes of statistical models is a plus. 
• Strong verbal and written communications skills, listening, cross-functional collaborations and effective presentation skills. This is essential since this role will have a lot of exposure to different internal groups (business functions, Data, IT, Legal, Risk, etc.) as well as third-party data vendors and consultants.

Source: https://worldbankgroup.csod.com/ats/careersite/JobDetails.aspx?id=29090&site=1

<!—

<!–

–>