Company Description NBCUniversal is one of the world's leading media and entertainment companies. We create world-class content, which we distribute across our portfolio of film, television, and streaming, and bring to life through our global theme park destinations, consumer products, and experiences. We own and operate leading entertainment and news brands, including NBC, NBC News, NBC Sports, Telemundo, NBC Local Stations, Bravo, and Peacock, our premium ad-supported streaming service. We produce and distribute premier filmed entertainment and programming through our powerhouse film and television studios, including Universal Pictures, DreamWorks Animation, and Focus Features, and the four global television studios under the Universal Studio Group banner, and operate industry-leading theme parks and experiences around the world through Universal Destinations & Experiences, including Universal Orlando Resort, home to Universal Epic Universe, and Universal Studios Hollywood. NBCUniversal is a subsidiary of Comcast Corporation. Visit www.nbcuniversal.com for more information. Our impact is rooted in improving the communities where our employees, customers, and audiences live and work. We have a rich tradition of giving back and ensuring our employees have the opportunity to serve their communities. We champion an inclusive culture and strive to attract and develop a talented workforce to create and deliver a wide range of content reflecting our world. NBCUniversal est l'un des leaders mondiaux du secteur des médias et du divertissement. Nous créons des contenus d'exception, que nous diffusons à travers notre portefeuille de films, de programmes télévisés et de services de streaming, et que nous donnons vie grâce à nos parcs à thème internationaux, nos produits grand public et nos expériences. Nous détenons et exploitons des marques de premier plan dans les domaines du divertissement et de l'information, notamment NBC, NBC News, NBC Sports, Telemundo, les chaînes locales NBC, Bravo et Peacock, notre service de streaming premium financé par la publicité. Nous produisons et distribuons des films et des programmes de divertissement de premier ordre grâce à nos puissants studios de cinéma et de télévision, notamment Universal Pictures, DreamWorks Animation et Focus Features, ainsi qu'aux quatre studios de télévision mondiaux regroupés sous la bannière Universal Studio Group. Nous exploitons également des parcs à thème et des expériences de premier plan à travers le monde via Universal Destinations & Experiences, notamment l'Universal Orlando Resort, qui abrite l'Universal Epic Universe, et Universal Studios Hollywood. NBCUniversal est une filiale de Comcast Corporation. Rendez-vous sur www.nbcuniversal.com pour plus d'informations. Notre impact repose sur l'amélioration des communautés dans lesquelles vivent et travaillent nos employés, nos clients et nos publics. Nous avons une riche tradition d'engagement social et veillons à ce que nos employés aient la possibilité de s'investir au sein de leurs communautés. Nous défendons une culture inclusive et nous nous efforçons d'attirer et de former une main-d'œuvre talentueuse afin de créer et de proposer un large éventail de contenus reflétant notre monde. Job Description We are seeking a Data Scientist with experience manipulating large tabular and user-behavior datasets. This role is centered on bridging the gap between raw data and high-quality machine learning inputs, requiring a blend of technical expertise and cross-functional leadership. Nous recherchons un(e) scientifique des données ayant de l'expérience dans l'exploitation de grands ensembles de données tabulaires et comportementales d'utilisateurs. Ce rôle vise à combler l'écart entre les données brutes et les entrées de haute qualité pour les modèles d'apprentissage automatique, en combinant expertise technique et leadership transversal. Vous jouerez un rôle clé en veillant à ce que les données soient correctement structurées, validées et alignées avec les objectifs produit et d'apprentissage automatique, afin de permettre le développement de modèles robustes et évolutifs. Responsibilities: - Cross-Functional Coordination: Work with partner ML and Product engineers and TPMs to spec out data and training requirements. - Data Strategy & Pipeline Oversight: Ensure that datasets are correctly curated, filtered, and processed to meet the rigorous standards of production-level machine learning. - Requirements Translation: Act as a technical translator, taking high-level project goals and turning them into actionable data specs for engineering and annotation teams. - Quality Assurance & Analysis: Maintain high standards for data integrity, ensuring that the behavioral datasets used for training are representative and accurate. Responsabilités principales - Collaboration interfonctionnelle : Travailler avec les ingénieurs ML, les équipes Produit et les TPM pour définir les besoins en données et en entraînement. - Stratégie des données et supervision des pipelines : S'assurer que les ensembles de données sont correctement sélectionnés, filtrés et traités afin de répondre aux exigences des systèmes d'IA en production. - Traduction des besoins : Transformer des objectifs produit de haut niveau en spécifications de données concrètes et exploitables. - Assurance qualité et analyse : Maintenir des normes élevées de qualité des données en garantissant leur exactitude, leur représentativité et leur fiabilité. Qualifications - Master's or Bachelor's Degree or certification in Data Science or related computational sciences field. - 3+ years of relevant industry experience in a fast paced, high growth tech environment. Professional Experience: Proven experience as a Data Scientist in a fast-paced environment. - Domain Context: Prior experience in industries with complex multi-disciplinary teams such as robotics, streaming services, game development, search engines, and eCommerce. Technical Proficiency - Core Tools: Fluency with Python, Git, and the Unix shell. - Ecosystem: Familiarity with collaborative tools such as Jira/Confluence, Slack, a Git server, and an experiment tracking framework. - Data Visualization: Familiarity with data visualization and inspection tools specifically designed for user behavior. - Fundamentals: Deep understanding of data science fundamentals and a strong mathematical background. Attributes - Conscientiousness: High attention to detail and commitment to data accuracy. - Communication: Ability to collaborate effectively across different engineering disciplines to define and execute technical requirements. Qualifications - Baccalauréat ou Maîtrise, ou certification en science des données ou dans un domaine connexe des sciences computationnelles. - Minimum de 3 ans d'expérience pertinente dans un environnement technologique dynamique et en forte croissance. - Expérience démontrée en tant que scientifique des données dans un environnement dynamique et en forte croissance. - Une expérience dans des secteurs multidisciplinaires complexes tels que la robotique, les plateformes de streaming, les jeux vidéo, les moteurs de recherche ou le commerce électronique est fortement valorisée. Compétences techniques - Outils principaux : Maîtrise de Python, Git et des environnements Unix. - Écosystème : Familiarité avec des outils tels que Jira, Confluence, Slack, les workflows Git et les plateformes de suivi d'expériences. - Visualisation des données : Expérience avec des outils dédiés à la visualisation et à l'analyse des comportements utilisateurs. - Fondamentaux : Solides connaissances en statistiques, en science des données et en mathématiques. Qualités recherchées - Rigueur : Grande attention aux détails et engagement envers la qualité et la précision des données. - Communication : Capacité à collaborer efficacement avec différentes équipes techniques et produit pour définir et exécuter les exigences techniques. Additional Information As part of our selection process, external candidates may be required to attend an in-person interview with an NBCUniversal employee at one of our locations prior to a hiring decision. NBCUniversal's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to AccessibilitySupport@nbcuni.com.

Who We Are: PureSpectrum is a rapidly growing market research and insights platform that simplifies technology, allowing researchers to gather and activate consumer data without disruption. As the go-to solution for high-quality multi-sourcing and fully automated research, PureSpectrum is helping to shape the future of insights. Our Marketplace facilitates over 65 million online interviews annually, and our proprietary respondent-level scoring system—PureScore—continues to set the industry standard for data quality and reliability. Recognized globally for both innovation and culture, PureSpectrum has been named one of Newsweek’s Global Most Loved Workplaces (2023–2025), included in Inc.’s Best Workplaces (2024-2025), certified as a Great Place to Work (2022–2025), and featured on Built In’s Best Places to Work list (2023–2025). PS is rapidly becoming the leading solution for quality multi-sourcing and end-to-end automated research solution. The Opportunity: We are looking for a Data Scientist to join our Data Science & AI team in Hyderabad. In this role, you will bring your deep expertise in fraud detection and threat mitigation, into the dynamic ecosystem of Market Research. We need a highly technical, hands-on builder who can architect real-time anomaly detection systems and isn't afraid to get into the weeds of feature engineering and distributed computing. Beyond core fraud detection, you will act as a technical leader and trusted advisor. You will design Agentic AI systems to automate process workflows, build core product analytics, and guide cross-functional teams (PMs and engineering) through modeling choices. You understand that deploying ML is as much a people and business challenge as it is a technical one, and you thrive in a high-velocity, dynamic environment. Location: Remote (mapped to Hyderabad, India) What You’ll Do - Architect Real-Time Risk & Fraud Systems: Design, train, and deploy high-throughput machine learning models to detect identity spoofing, survey fraud, and bot nets. Expand these capabilities into broader cybersecurity risk scoring, threat intelligence, and vendor risk assessments. - Process large scale transaction data: Build robust, distributed data pipelines to ingest massive transaction volumes. Perform deep exploratory data analysis (EDA) to identify complex behavioral patterns and anomalies. - Lead Technical Groundwork & Best Practices: Take ownership of the end-to-end ML lifecycle. Drive engineering excellence by actively contributing to code reviews, system design discussions, and establishing robust data science methodologies across the team. - Cross-Functional Prototyping & Expansion: Translate ambiguous customer and business needs into concrete ML solutions. Design and build prototypes across varied platform use cases, optimizing data quality and sample delivery. Design and interpret back tests or offline evaluations for ML and rules-based systems. - Drive Agentic AI Innovation: Build autonomous AI agents (leveraging LLMs and RAG) to monitor external channels (e.g., scraping online forums for threat intelligence), enforce data quality, and automate operational overhead like code documentation. - Advise & Communicate: Effectively communicate modeling choices, trust, and interpretability while delivering demos, executive presentations, and clear rollout plans. What You Bring (Must-Haves) - Education: Advanced degree (Master’s) in a quantitative STEM field (Computer Science, Statistics, Mathematics, Engineering, Physics) or equivalent professional experience solving complex analytical problems. - Experience: 5+ years of hands-on, production-level experience applying data science to real-world challenges, ideally within a high-growth tech, cybersecurity, or product-driven startup environment. - Advanced ML & Stats Fundamentals: Deep theoretical and practical knowledge of statistical modeling, anomaly detection, evaluation metrics, and experimentation frameworks. - Programming Mastery: Production-level coding proficiency in Python and advanced SQL. - Cloud & ML Frameworks: Deep expertise with traditional ML libraries (Scikit-learn, XGBoost) and modern cloud-based MLOps pipelines (AWS, GCP, Databricks, MLFlow). - Domain Expertise: A proven track record in fraud detection, cybersecurity, threat intelligence, or risk scoring. - Communication & Leadership: Excellent stakeholder-management skills. You are comfortable navigating diverse teams, partnering with product management, and communicating complex findings to non-technical audiences. Nice-to-Haves - GenAI & LLMs: Genuine enthusiasm and hands-on exposure to modern LLMs, modern modeling approaches, and deploying Agentic AI for business workflows. - Intellectual Curiosity: A visible track record of your craft via GitHub profile showcasing personal ML/AI projects, open-source contributions, research publications, hackathon participation or strong rankings in Kaggle competitions (especially in fraud or anomaly detection tracks). PureSpectrum Perks: PureSpectrum is continuously focused on our culture, which is rooted in innovation, connection, and providing a great experience at all business levels —what we like to call PSX. Our team enjoys a creative and collaborative environment with plenty of opportunities for fun, connection, and team celebrations. - We foster a modern, collaborative and inclusive culture that values flexibility, creativity, and open communication. - Our team enjoys a competitive compensation and benefits package, including comprehensive health insurance, Provident Fund (PF), and other perks that support overall well-being. - We offer a robust leave policy covering casual, sick, and vacation leaves, along with special leaves for key life events. - Regular team events, celebrations, and engagement activities strengthen our sense of community and belonging. - At PureSpectrum, you’ll find a relaxed yet high-performing workplace where you can grow professionally, build meaningful connections, and truly be yourself. We’re committed to supporting our team both personally and professionally—empowering every team member to thrive inside and outside of work. Diversity & Inclusion PureSpectrum is proud to be an equal opportunity employer. We welcome candidates from all backgrounds and do not discriminate based on race, colour, religion, gender, gender identity, sexual orientation, age, disability, marital status, or any other characteristic protected by law.

• Diseñar, desarrollar e implementar modelos de machine learning y deep learning para analítica predictiva y clasificación. • Desarrollar y ajustar soluciones de NLP, incluyendo trabajo con LLMs. • Realizar análisis de datos avanzados para la identificación de insights y soporte a decisiones estratégicas. • Escribir código eficiente y escalable en Python y PySpark. • Utilizar SQL para extracción, manipulación y consulta de grandes volúmenes de datos. • Construir y desplegar modelos mediante servicios de AWS (SageMaker, Glue, Lambda, entre otros). • Colaborar con equipos de data engineers, data analysts y stakeholders. • Mantenerse al día en tendencias y tecnologías de data science, IA y cloud computing.

Role Description Collaborate with cross-functional partners in operations, finance, marketing, and engineering to understand business imperatives and scope data science projects. - Explore possibilities to solve the business imperatives by identifying data sources, creating data where needed, and applying data science techniques. - Work with VP Data, VP of Analytics, and CFO to create data-informed business strategies and roadmaps. - Translate data needs into data product requirements, evaluate technologies, and identify opportunities to innovate and improve data science capabilities. - Use creative problem-solving skills to analyze data and build statistical/machine learning models to help solve business problems from different perspectives. - Work with data engineering lead to create services that can ingest and supply data to and from both internal and external sources and ensure data quality and timeliness. - Build the data science team and lead in data scientist recruitment process. - Guide and coach data scientists and own the deliverables of data visualization and dashboards to help the organization monitor performance, generate insights, and continuously improve user experience. - Continuously grow the data science team’s skillsets. - Establish playbooks to drive data product development process and consistent outcomes. - Use strong communication skills (written and verbal) to lead the full lifecycle of model development, which spans from business problem discovery, data discovery to model deployment and monitoring. - Evangelize data science across the entire company; identify and make the business case for data science based use cases. - Where needed, conduct hands-on wrangling, processing, cleansing, and verifying data from different sources used for analysis. - Analyze data with complex relationships, hierarchical levels, and time series, such as Pandas, PySpark. - Use and recommend a wide range of machine learning algorithms and statistical modeling, including latest LLM developments. - Utilize data visualization and dashboard tools, such as Tableau, PowerBI, and Snowflake. - Up to 10% domestic travel required for meetings/client visits; 100% remote; must reside in U.S.; reports to HQ in New York, NY. - Salary: $336,350 - $356,350 per year. Qualifications - Bachelor’s Degree or U.S. equivalent in Quantitative Methods, Statistics, Econometrics, or related field. - 5 years of professional experience as a Data Scientist, Operations Research Analyst, or any occupation, job title, or position leading a data science team in a technology organization. Requirements - 5 years of professional experience implementing data science solutions by identifying relevant data sources, creating data pipelines, and applying advanced data science techniques to support business decision-making. - 5 years of professional experience designing and developing machine learning models and statistical algorithms to analyze structured and unstructured data from both internal and external sources. - 5 years of professional experience collaborating with cross-functional teams to gather business requirements, define technical scopes, and deliver actionable data insights. - 5 years of professional experience utilizing tools and libraries including Python, SQL, Spark, PyTorch, Pandas, and PySpark to perform data wrangling, cleansing, and advanced analytics. - 5 years of professional experience developing and maintaining data visualization dashboards using tools including Tableau to monitor performance and communicate insights to stakeholders. - 5 years of professional experience establishing scalable data product development processes through consistent use of playbooks, code standards, and reproducible pipelines. - 5 years of professional experience leading the full lifecycle of machine learning models from business problem discovery to model deployment and performance monitoring. - 5 years of professional experience evangelizing data science practices across organizations, including coaching team members, supporting recruitment efforts, and promoting a data-driven culture. Contact Apply online at fanaticsinc.com/careers or email resume to: WorkWithFanatics@FanaticsInc.com . Must specify Ad Code ZCKM in subject line.