• Lead the design, development, and deployment of scalable machine learning solutions focused on pricing optimization, demand forecasting, and promotion planning. • Build and improve statistical and machine learning models for: - Demand forecasting - Price elasticity modeling - Promotion optimization - Inventory and revenue forecasting • Design, build and deploy robust ML pipelines in Databricks, build model monitoring systems, and production-ready APIs. • Ability to design and evaluate transformer-based time series forecasting models for large-scale retail sales forecasting and demand planning. • Drive experimentation, model evaluation, and continuous improvement of forecasting and pricing models. • Analyze large-scale structured and unstructured retail datasets to uncover trends, customer behavior patterns, and pricing insights. • Develop data-driven strategies that help maximize revenue, profitability, and pricing efficiency across products and categories. • Apply advanced statistical techniques and machine learning algorithms to solve complex retail business problems. • Collaborate closely with Product, Engineering, Data Engineering, and Business teams to translate business requirements into scalable ML solutions. • Mentor junior data scientists and provide technical guidance across cross-functional teams. • Communicate analytical findings and business recommendations clearly to both technical and non-technical stakeholders.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Associate Managing Consultant, Strategy and Transformation - Generative AI Engineer / Generative AI Data Scientist Advisors & Consulting Services Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution. Our Advisors & Consulting Services team combines traditional management consulting with Mastercard's rich data assets, proprietary platforms, and technologies to provide clients with powerful strategic insights and recommendations. Our teams work with a diverse global customer base across industries, from banking and payments to retail and restaurants. The Advisors & Consulting Services group has five specializations: Strategy & Transformation, Performance Analytics, Business Experimentation, Marketing, and Program Management. Our Strategy & Transformation consultants lead clients through impactful decision-making as they tackle strategic, tactical, operational, and transformational business challenges. They apply a broad set of problem-solving techniques to improve the client's overall strategy, performance, and operations. Job Summary We are seeking a Technical Consultant who combines strong hands-on GenAI engineering capability with solid data analytics and data science foundations, and the mindset of a trusted consultant. This is an experienced individual contributor role where you will design, build, and deploy production-grade Generative AI solutions for enterprise clients, while also contributing to broader data analytics and data science initiatives where GenAI is not always the right answer. You will operate at the intersection of advanced AI engineering, analytical problem-solving, and client advisory, translating ambiguous business problems into scalable, measurable solutions. You will be expected to contribute and take increasing ownership across the end-to-end delivery: from shaping the problem with stakeholders, to building and productionizing systems, to supporting adoption and handover - with support from senior team members where needed. The ideal candidate is comfortable switching between LLM-centric systems and classical analytics/modelling and can communicate confidently with both technical and non-technical audiences. Key Responsibilities: 1. End-to-End GenAI Solution Delivery • Lead the design, development, and deployment of Generative AI solutions using LLMs, Agentic Designs and Multi-Agent Systems taking full ownership of delivery outcomes, timelines, and quality. • Translate business problems into well-architected GenAI systems that deliver clear, measurable value. 2. GenAI System Architecture & Engineering • Design and implement scalable GenAI systems, including Retrieval-Augmented Generation (RAG) pipelines, vector database integrations, and API-driven architectures. • Design systems that balance performance, cost, security, and maintainability in enterprise environments. 4. Productionalization & LLMOps • Establish CI/CD pipelines and operational practices for GenAI solutions, ensuring reliability, observability, and cost efficiency. • Work within cloud-native environments to deploy and monitor production AI systems. 5. Data Analytics & Data Science Contribution • Support broader analytics and data science initiatives, including exploratory analysis, descriptive and diagnostic analytics, and predictive modeling where required. • Apply sound statistical and analytical judgment to complement GenAI-driven approaches. 6. Rapid Prototyping & Storytelling • Build interactive demos and lightweight applications to validate ideas, gather stakeholder feedback, and accelerate decision-making. • Clearly communicate technical concepts, trade-offs, and insights to non-technical stakeholders. 7. Consulting & Stakeholder Engagement • Act as a trusted advisor to clients and internal teams, helping shape problem statements, success metrics, and solution approaches. • Collaborate effectively across multidisciplinary teams and contribute to a high standard of consulting delivery. 8. Documentation & Handover • Produce clear technical documentation and ensure smooth handover of solutions to permanent teams or client owners. Required Qualifications & Skills Experience • 4-7 years of professional experience in software engineering, data science, or applied machine learning. • At least 2 years of hands-on experience building and deploying Generative AI or LLM-based solutions in real-world environments. Core GenAI Expertise • Practical experience working with major LLMs (e.g. GPT, Claude, Llama) via APIs and open-source frameworks. • Proven experience designing and optimizing RAG systems using tools such as LangChain or LlamaIndex. • (Preferred) Understanding of fine-tuning, prompt engineering, and evaluation techniques, including their trade-offs. Data Analytics & Data Science • Strong ability to analyze large datasets and synthesize insights using Python and modern analytics libraries. • Experience with descriptive analytics, business intelligence, and applied modeling to inform decision-making. • Solid understanding of metrics, benchmarking, and measurement in complex business contexts. Technical Proficiency • Advanced Python proficiency and experience with relevant ML/AI libraries. • (Preferred) Experience with vector databases (e.g. Pinecone, Chroma, Milvus) and embedding models. • (Preferred) Hands-on experience deploying solutions on cloud platforms (AWS, Azure, or GCP), including managed AI services. • (Preferred) Experience building prototypes and simple UIs using tools such as Streamlit, Gradio, Flask, or FastAPI. Front-end frameworks (React, Vue) are a plus. Consulting & Delivery Mindset • Proven ability to work directly with clients or senior stakeholders. • Strong sense of ownership, autonomy, and accountability for delivery outcomes. • Excellent communication skills, with the ability to explain complex ideas clearly and pragmatically. Education • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field (preferred). This role is not a research-only position, and it is not limited to prompt engineering or experimentation. You will be expected to build production-ready systems and engage directly with business stakeholders. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: - Abide by Mastercard's security policies and practices; - Ensure the confidentiality and integrity of the information being accessed; - Report any suspected information security violation or breach, and - Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

Role Description Responsibilities include variant analysis of diagnostic molecular genetic test results; evaluation of published literature, clinical data and review of both functional and in silico data to provide accurate, thorough, and thoughtful clinical interpretation of results. - Write research articles in collaboration with other medical professionals and colleagues outside and inside the organization, if data is relevant to the scientific community. - Additional responsibilities as designated by supervisor/manager and/or with increasing seniority (Senior Variant Assessment Scientist). - Write and interpret molecular test results, including relevant medical literature reviews and summary. - Participate in updating variant classification guidelines and developing gene specific classification guidelines. - Research novel ways to assess sequence variants. - Manage and follow guidelines of variant pre-classification workflow to maximize reporting results within published turn-around times. - Train new variant team members or clinical team. Qualifications - PhD and/or MD with expertise in molecular genetics, human genetics, molecular pathology or related field. - MS in molecular biology, genetics or related field with exceptional expertise and outstanding job performance may also be considered. Requirements - Thorough and ongoing knowledge of current theories and principles of human genetics. - Excellent written and verbal communication skills to convey difficult information in a clear, kind, and respectful manner. - Willingness and ability to work in and contribute to a fast-paced, highly collaborative environment. - Prior experience in variant assessment and reporting specialty preferred. - Minimum +2 years of experience with variant assessment. Company Description

Role Description En Personal Pay estamos sumando un/a Sr. Data Scientist donde combinamos tecnología, innovación y datos para desarrollar soluciones financieras que simplifican la vida de las personas. Buscamos protagonistas que se animen a: - Contribuir al desarrollo de soluciones de analítica avanzada con impacto transversal en la compañía, mediante la implementación de modelos de aprendizaje automático supervisados y no supervisados, orientados a predecir comportamientos clave del cliente en una empresa fintech. - Analizar y evaluar los resultados de las soluciones, ajustándolas según sea necesario para mejorar su performance. - Trabajar en el monitoreo y mantenimiento de los modelos implementados, asegurando su rendimiento continuo y su alineación con los objetivos del negocio. - Manipulación de datos utilizando lenguajes de programación y bases de datos. - Colaborar con el resto de las áreas de la gerencia para comprender los requisitos del negocio y diseñar soluciones que estén acorde a la metodología para su automatización y puesta en producción. - Será valorado conocimientos en Inteligencia Artificial Generativa para abordar problemas específicos y desarrollar soluciones innovadoras. - Traducir las necesidades de los stakeholders para desarrollar soluciones analíticas que mejoren los procesos de negocio y sean soporte para la toma de decisiones. Qualifications - Graduados de las carreras de Económicas / Estadística / Ciencias Exactas / Actuario / Sistemas / Ciencias de la Computación o educación y experiencia equivalentes. - Posgrado / Master en minería de datos, ciencia de datos o similar (deseable). - +2 años de experiencia como Data Scientist o en roles similares. - Dominio de técnicas estadísticas y herramientas de ML y Big Data. - Entrenamiento, validación e implementación de algoritmos de ML. - Conocimientos avanzados y experiencia en el uso de lenguajes de programación para manipular y extraer datos (Python, SQL). - Experiencia trabajando en entornos Cloud (GCP, AWS, Azure). Benefits - Modalidades de trabajo flexible. - Bono por performance. - Una semana extra de vacaciones. - Descuentos y bonificaciones exclusivas en nuestras marcas Personal y Flow (internet, conectividad móvil y entretenimiento) para vos y tu familia. - Prepaga para vos y tu grupo familiar a cargo. - Acceso libre a la plataforma digital de contenidos de aprendizaje. - Bonificaciones especiales en universidades de primer nivel. - Programa de referidos con reconocimiento económico. - ¡Y mucho más!