217 Model Development Jobs - Page 4

Understand business objectives and translate them into data and machine learning requirements Identify what data is needed to support specific AI use cases and assess its availability, quality and structure Explore and profile data from various sources to evaluate its suitability and uncover biases, gaps or integration challenges Visualising data and analytical results using tools such as Power BI, with the ability to create insightful dashboards for both technical and non-technical audiences. Collaborate with data owners and engineers to locate, access and prepare data for experimentation and model development Work closely with product teams to define success metrics and ensure data can support reliable measurement and evaluation Support the design of data flows and contribute to ingestion and preparation strategies that align with modelling needs Translate insights from data exploration and model experimentation into clear actionable recommendations Contribute to best practices related to data validation, model documentation and governance of analytical workflows Collaborate with ML engineers and AI architects to assess modelling options and design evaluation strategies Stay up to date with developments in AI and machine learning and actively share insights with the wider team Qualification Your starting point for constant growth From the moment you join Ramboll, we will support your personal and professional development so that you grow with the company. For this role, we believe your starting point is: A master’s degree in data science, computer science, statistics, applied mathematics or a related field Strong experience in applied data science or machine learning, with an emphasis on data readiness and problem framing Proficiency in Python and experience with common data science libraries (e.g., pandas, scikit-learn, TensorFlow or PyTorch) Demonstrated ability to explore, profile and assess complex data sets to determine their value for ML solutions Experience working with business stakeholders to translate objectives into data needs and analytic plans Understanding of how data flows from source systems into models, and experience partnering with data engineers to build effective pipelines Excellent communication skills, with the ability to explain and visualize data-related concepts to non-technical audiences Fluency in English Additional Information We offer: Competitive salary and benefits package. Opportunities for professional growth and development. Flexible work environment and work-life balance. A multi-cultural work environment Personal qualities that will help you succeed in this role include: Ability to collect and analyse data, establish facts and make recommendations in written and verbal form. Ability to explain and translate complex, technical IT requirements into material understandable for non-IT staff. Ability to liaise with all parts of an organisation, including IT and business stakeholders. Open-minded and helpful and, finally, a good portion of self-awareness and humour.

Name List Screening and Transaction Screening Model Strats, AS Role Description Group Strategic Analytics (GSA) is part of Group Chief Operation Office (COO) which acts as the bridge between the Banks business and infrastructure functions to help deliver the efficiency, control, and transformation goals of the Bank. You will work within the Global Strategic Analytics Team as part of a global model strategy and deployment of Name List Screening and Transaction Screening. To be successful in that role, you will be familiar with the most recent data science methodologies and have a delivery-centric attitude, strong analytical skills, and a detail-oriented approach to breaking down complex matters into more understandable details. The purpose of Name List Screening and Transaction Screening is to identify and investigate unusual customer names and transactions and behavior, to understand if that activity is considered suspicious from a financial crime perspective, and to report that activity to the government. You will be responsible for helping to implement and maintain the models for Name List Screening and Transaction Screening to ensure that all relevant criminal risks, typologies, products, and services are properly monitored. We are looking for a high-performing Associate in financial crime model development, tuning, and analytics to support the global strategy for screening systems across Name List Screening (NLS) and Transaction Screening (TS). This role offers the opportunity to work on key model initiatives within a cross-regional team and contribute directly to the banks risk mitigation efforts against financial crime. You will support model tuning and development efforts, support regulatory deliverables, and help collaborate with cross-functional teams including Compliance, Data Engineering, and Technology. Your key responsibilities Support the design and implementation of the model framework for name and transaction screening including coverage, data, model development and optimisation. Support key data initiatives, including but not limited to, data lineage, data quality controls, and data quality issues management. Document model logic and liaise with Compliance and Model Risk Management teams to ensure screening systems and scenarios adhere to all model governance standards Participate in research projects on innovative solutions to make detection models more pro-active Assist in model testing, calibration and performance monitoring. Ensure detailed metrics & reporting are developed to provide transparency and maintain effectiveness of name and transaction screening models. Support all examinations and reviews performed by regulators, monitors, and internal audit Your skills and experience Advanced degree (Masters or PhD) in a quantitative discipline (Mathematics, Computer Science, Data Science, Physics or Statistics) 1-3 years experience in data analytics or model development (internships included). Proficiency in designing, implementing (python, spark, cloud environments) and deploying quantitative models in a large financial institution, preferably in Front Office. Hands-on approach needed. Experience utilizing Machine Learning and Artificial Intelligence Experience with data and the ability to clearly articulate data requirements as they relate to NLS and TS, including comprehensiveness, quality, accuracy and integrity Knowledge of the banks products and services, including those related to corporate banking, investment banking, private banking, and asset management

This job will drive the strategic vision and development of cutting-edge BNPL credit models and collection models across all products . The incumbent will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. The role involves building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences. Your way to impact - Manage multiple priorities through solid project management practices. Maintain strong presence in our India sites and help keep PayPal a great place to work. Your day to day - Define and drive the strategic vision for machine learning initiatives across multiple teams or projects. Lead the development and optimization of state-of-the-art machine learning models. Oversee the preprocessing and analysis of large datasets. Deploy and maintain ML solutions in production environments. Collaborate with cross-functional teams to integrate ML models into products and services. Monitor and evaluate the performance of deployed models, making necessary adjustments. Mentor and guide junior engineers and data scientists. Publish research findings and contribute to industry discussions. Lead the development of new methodologies and frameworks for ML applications. What do you need to bring- Minimum of 15 years of relevant work experience and a Bachelors degree or equivalent experience. Minimum of 3 years management experience Deep experience in AI/ML model development, with a proven track record in financial services Experience in setting up nurturing large AI / ML teams Advanced degree in Computer Science, Engineering, Statistics, or a related field. Exceptional communication skills, with the ability to articulate complex technical concepts to nontechnical stakeholders and executives. Strong connections with the AI/ML ecosystem in India is a plus

We are seeking a highly skilled Data Scientist who specializes in MLOps to join our team. The successful candidate will be responsible for the development, deployment, and automation of machine learning models. This role requires a deep understanding of machine learning operations (MLOps) to ensure efficient and scalable model management. Additionally, expertise in time series forecasting and Flask for web applications is desired. Model Development and Deployment: Design, develop, and deploy machine learning models tailored to large datasets. Ensure models are scalable and production-ready, capable of handling real-world data and scenarios. Automation: Implement automation processes for model training, testing, and deployment. Develop and maintain CI/CD pipelines for continuous integration and delivery of machine learning models. End-to-End Workflows: Create and manage end-to-end workflows for machine learning projects, from data collection and preprocessing to model deployment and monitoring. Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and workflows. Time Series Forecasting: Develop and implement time series forecasting models to predict future trends and patterns. Utilize statistical and machine learning techniques to improve forecasting accuracy. Web Applications with Flask: Develop web applications using Flask to provide user-friendly interfaces for machine learning models. Integrate machine learning models into web applications to enable real-time predictions and insights. Monitoring and Visualization: Use tools like Splunk to monitor model performance and visualize data insights. Implement monitoring solutions to track model accuracy, performance, and drift over time. Qualifications: Proven experience in developing machine learning solutions for large datasets. Strong expertise in MLOps, including model development, deployment, and automation. Proficiency in programming languages such as Python. Experience with machine learning frameworks and libraries (eg, TensorFlow, PyTorch, Scikit-learn). Expertise in time series forecasting techniques and tools. Experience with Flask for developing web applications. Familiarity with monitoring and visualization tools like Splunk. Excellent problem-solving skills and the ability to work in a collaborative environment. Primary Skills: Core: Data Scientist with MLOps Expertise Data Science and Analytics - One to Three Years Project Manager - One to Three Years MLOps - One to Three Years PSP Defined SCU: Data Engineering_Senior Data Ops Professional

Some careers have more impact than others. We are currently seeking an experienced professional to join our team in the role of Assistant Vice President, Model Risk Governance and Stewardship Principal responsibilities Supporting the setting of the firm s model risk policies and procedures. Supporting reviews to ensure policy is implemented effectively across businesses and functions. Producing and providing Model Risk Reporting on a regular basis. Supporting the development of appropriate training materials. Suggest enhancements to systems, tooling and/or working practices to improve efficiency. Prepare the related model risk governance reporting. Support the development of appropriate Model Risk Governance procedures, tools and management information. Work with colleagues in 1LOD(Line of Defense), 2LOD and 3LOD to deliver the broader set of Global Model Risk Governance deliverables. Contribute to management, regulatory, and external confidence in all models used across the group. Support the management of model risk across a large complex banking group. Support model risk whilst significant transformational activity is being implemented, both regionally and globally. Operate within a changing and rapidly developing regulatory environment. Continually support HSBCs approach to conduct and cultivate a positive risk aware culture, which is designed to ensure we deliver fair outcomes for our customers and do not disrupt the orderly and transparent operation of financial markets. Requirements Experience of model risk management, governance and/or model development / validation. Understanding of Risk Management Framework, Risk Controls is mandatory Experience of local regulators and regulations would be an advantage. Some knowledge and expertise of local market and HSBC s different business lines is preferable. 5-10 years of professional experience in risk management would be preferable. Experience to be able to identify and implement process improvements. Ability to develop strong networks with key stakeholders at all points in a matrix structure, creating an ability to execute task at hand with minimum conflict. Providing expert advice, robust challenge and managing risk and controls Strong written and oral communication skills. Attention to detail. Team-oriented mentality combined with ability to complete tasks independently to a high-quality standard. You ll achieve more at HSBC HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.

What you need to know about the role This job will drive the strategic vision and development of cutting-edge BNPL credit models and collection models across all products . The incumbent will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. The role involves building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences. Job Description Your way to impact - Manage multiple priorities through solid project management practices. Maintain strong presence in our India sites and help keep PayPal a great place to work. Your day to day - Define and drive the strategic vision for machine learning initiatives across multiple teams or projects. Lead the development and optimization of state-of-the-art machine learning models. Oversee the preprocessing and analysis of large datasets. Deploy and maintain ML solutions in production environments. Collaborate with cross-functional teams to integrate ML models into products and services. Monitor and evaluate the performance of deployed models, making necessary adjustments. Mentor and guide junior engineers and data scientists. Publish research findings and contribute to industry discussions. Lead the development of new methodologies and frameworks for ML applications. What do you need to bring- Minimum of 15 years of relevant work experience and a Bachelors degree or equivalent experience. Minimum of 3 years management experience Deep experience in AI/ML model development, with a proven track record in financial services Experience in setting up & nurturing large AI / ML teams Advanced degree in Computer Science, Engineering, Statistics, or a related field. Exceptional communication skills, with the ability to articulate complex technical concepts to nontechnical stakeholders and executives. Strong connections with the AI/ML ecosystem in India is a plus.

: Job Title- Name and Transaction Screening Model Strats, AVP Location- Bangalore, India Role Description Group Strategic Analytics (GSA) is part of Group Chief Operation Office (COO) which acts as the bridge between the Banks business and infrastructure functions to help deliver the efficiency, control, and transformation goals of the Bank. You will work within the Global Strategic Analytics Team and lead a team of 5 Associates to support a global model strategy and deployment of Name & Transaction Screening. To be successful in that role, you will be familiar with the most recent data science methodologies and have a delivery-centric attitude, strong analytical skills, and a detail-oriented approach to breaking down complex matters into more understandable details. You will work in a collaborative global team and focus on people development and career growth. The purpose of Name & Transaction Screening is to identify and investigate clients and customer transactions that come into scope per sanctions screening requirements, to understand if that activity is considered suspicious from a financial crime perspective, and to report that activity to the government. Reporting to the Name & Transaction Screening Lead within Trader and Client Control Strats, you will be responsible for implementing and maintaining the models for Name & Transaction Screening. You will help ensure that all relevant criminal risks, typologies, products, and services are properly monitored. We are looking for a high-performing Assistant Vice President with 5+ years of experience in financial crime model development, tuning, and analytics to support the global strategy for screening systems across Name Screening (NLS) & Transaction Screening (TS). This role offers the opportunity to drive key model initiatives within a cross-regional team and contribute directly to the banks risk mitigation efforts against financial crime. You will drive model tuning and development efforts, support regulatory deliverables, and collaborate with cross-functional teams including Compliance, Data Engineering, and Technology. What well offer you As part of our flexible scheme, here are just some of the benefits that youll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your key responsibilities Model Development & Tuning Manage a team of 5 Associates to support the design and calibration of models for NLS and TS systems, ensuring optimal detection quality and manageable alert volumes. Support data exploration, feature engineering, and statistical analysis to inform tuning strategies. Document model logic, decisions, and outcomes in line with governance and validation standards. Project Engagement Contribute to specific model projects, from requirements gathering through to development, testing, and implementation. Coordinate small teams or working groups for agile delivery, working with developers, QA, and operations stakeholders. Performance Monitoring & Validation Support Monitor model performance metrics and investigate anomalies in production environments. Partner with model validation and internal audit to respond to queries and provide supporting analysis. Stakeholder Engagement Liaise with regional Compliance teams and operational users to gather feedback on model effectiveness. Contribute to presentations and technical reports for governance forums and senior stakeholders. Process Improvement Contribute to continuous improvement of the model development framework and documentation standards. Proactively identify opportunities for automation, efficiency, or application of advanced analytics. Your skills and experience Experience: 5+ years in model development, risk analytics, or quantitative compliance, preferably within financial crime or sanctions screening. Familiarity with financial crime systems (e.g., Actimize, Fircosoft, or equivalent platforms) and regulatory frameworks (e.g., AMLD, OFAC, FCA guidance). Technical Skills: Recent and relevant hands-on experience in SQL, Python for data analysis and model development. Strong Excel and data visualization skills; experience using Power BI or Tableau is a plus. Understanding of statistical techniques such as threshold optimization, precision/recall, ROC curves. Soft Skills: Strong analytical and problem-solving abilities. Ability to communicate complex technical content to non-technical stakeholders. Highly organized, with strong attention to detail and documentation quality. How well support you Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs About us and our teams Please visit our company website for further information: https://www.db.com/company/company.htm We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively. Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group. We welcome applications from all people and promote a positive, fair and inclusive work environment.

Key Responsibility: End-to-End Model Development Design, train, and deploy machine learning models (supervised/unsupervised learning, NLP, time-series forecasting) using Python (scikit-learn, TensorFlow, PyTorch) and R for specialized statistical analysis. Optimize models for computational efficiency via parallelization, quantization, and cloud-native architectures (AWS SageMaker, GCP Vertex AI). Data Engineering & Pipeline Automation Build robust ETL/ELT pipelines for structured/unstructured data using SQL, Spark, and Apache Airflow. Implement feature engineering workflows and ensure data quality for large-scale datasets (1M+ records). Cross-Functional Collaboration Partner with product, risk, and engineering teams to operationalize models into business applications (e.g., credit risk systems, customer segmentation tools). Mentor junior engineers and lead code reviews to maintain best practices in MLops workflows. Model Governance & Compliance Develop monitoring frameworks for model drift, bias detection, and performance degradation. Ensure compliance with regulatory standards and internal governance policies. Innovation & Research Stay ahead of industry trends (e.g., LLMs, generative AI) and prototype solutions using no-code platforms. Publish internal white papers on novel methodologies and present findings to stakeholders. Technical Requirements Core Skills: Python (expert), R (intermediate), SQL, Apache Spark, Apache Arrow, Pydantic Machine Learning: Regression, classification, clustering, deep learning (CNNs, RNNs) Frameworks: scikit-learn, PyTorch, TensorFlow, Hugging Face, MLflow Cloud: AWS/GCP/Azure or any cloud platform, Docker, Kubernetes Domain Expertise (Preferred): Financial services (PD/LGD modelling, ECL calculations, risk analytics) Experience with no-code platforms is a bonus Knowledge of regulatory frameworks (Basel III, IFRS 9) Soft Skills & Culture Fit Ownership Mindset: Take end-to-end responsibility for projects, from ideation to deployment. Collaboration: Excel in cross-functional teams with clear communication to technical and non-technical stakeholders. Innovation: Continuously explore emerging tools (e.g., LLMs, AutoML) to solve business challenges.

Roles and Responsibilities Develop credit risk models using SAS, SQL, and statistical modeling techniques to predict defaults, losses, and other credit-related metrics. Collaborate with cross-functional teams to design and implement effective credit risk strategies that meet business objectives. Conduct stress testing and scenario analysis to identify potential risks and opportunities for growth. Provide data insights and recommendations to stakeholders on loss forecasting, scorecards, and portfolio performance. Desired Candidate Profile 2+ years of experience in Credit Risk Modelling/Analytics or related field. Strong expertise in Basel II/III regulations, CECL/CCAR requirements under IFRS9 framework. Proficiency in programming languages such as Python/R/SAS; strong understanding of machine learning algorithms an added advantage.

Roles and Responsibilities Develop credit risk models using SAS, SQL, and statistical modeling techniques to predict defaults, losses, and other credit-related metrics. Collaborate with cross-functional teams to design and implement effective credit risk strategies that meet business objectives. Conduct stress testing and scenario analysis to identify potential risks and opportunities for growth. Provide data insights and recommendations to stakeholders on loss forecasting, scorecards, and portfolio performance. Desired Candidate Profile 2+ years of experience in Credit Risk Modelling/Analytics or related field. Strong expertise in Basel II/III regulations, CECL/CCAR requirements under IFRS9 framework. Proficiency in programming languages such as Python/R/SAS; strong understanding of machine learning algorithms an added advantage.

Salary : 20 to 35 LPA Exp: 3 to 8 years Location :Noida/Gurugram/Bangalore Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Join a multidisciplinary team of scientists, engineers, and mathematicians developing catastrophe models for the insurance and reinsurance industries. At Verisk, we are leading the way in generating new solutions based on machine learning and high-resolution numerical weather models to simulate the full distribution of possible extreme weather events cyclones, storm surge, convective storms, and flooding consistent with a changing climate. We are seeking a statistician or atmospheric scientist to advance the development, support, and delivery of the hazard component of atmospheric peril models. Your work will inform risk and capital management decisions globally. Qualifications Expertise in spatial statistics and extreme value analysis Strong understanding of atmospheric dynamics and extremes Experience with dynamic downscaling methods Proficiency in Python Clear written and verbal communication Practical, solution-focused mindset Requirements Ph.D. in statistics, atmospheric science, or a related field; or Master s with 3+ years of relevant experience Key Responsibilities Improve the accuracy of representing atmospheric perils Contribute to model development, validation, and productization for global clients Support model development using observational and reanalysis products, GCMs, and high-resolution simulations

Join a multidisciplinary team of scientists, engineers, and mathematicians developing catastrophe models for the insurance and reinsurance industries. At Verisk, we are leading the way in generating new solutions based on high-resolution numerical weather models to simulate the full distribution of possible extreme weather events cyclones, storm surge, convective storms, and flooding consistent with a changing climate. We are seeking an oceanographer or atmospheric scientist to advance the development, support, and delivery of the hazard component of storm surge peril models. Your work will inform risk and capital management decisions globally. Qualifications Hydrodynamic numerical modeling expertise with a focus on atmospheric phenomena - Experience in running Delft3D FM is a plus Strong understanding of the balance of model accuracy and computational cost Advance programming skills, with a preference for Python Expertise in a Linux based high performance computing environment Proficiency in version controlling systems (e.g. Git) Excellent written and verbal communication skills, with the ability to convey technical concepts clearly. A solutions-oriented mindset with a focus on delivering scalable, high-quality solutions. Proficiency in model calibration techniques to match observed data Experience validating model against historical datasets Experience in quality checking observational datasets and quantifying their uncertainty Version control in Git Geospatial analysis Requirements Ph.D. in oceanography or atmospheric science, or a related field; or Master s with 3+ years of relevant experience Key Responsibilities Provide domain knowledge and numerical modeling expertise for capturing storm surge processes Contribute to pioneering storm surge research, by making use of innovative scientific and statistical methods for model development, validation, and productization for global clients Develop and maintain codebase, apply version control (e.g. Git) best practices

Join a multidisciplinary team of scientists, engineers, and mathematicians developing catastrophe models for the insurance and reinsurance industries. At Verisk, we are leading the way in generating new solutions based on machine learning and high-resolution numerical weather models to simulate storm surge inundation consistent with a changing climate. We are seeking an oceanographer or statistician to advance the expansion, support, and delivery of the hazard component of storm surge peril models. Your work will inform risk and capital management decisions globally. Qualifications Expertise in physics-informed machine learning algorithms Proficiency in deep learning architectures, particularly Convolutional Neural Networks and Recurrent Neural Networks Experience in handling large, complex datasets for efficient utilization Strong understanding of data engineering for model training Experience in a Linux based high performance computing environment Excellent written and verbal communication skills, with the ability to convey technical concepts clearly. A solutions-oriented mindset with a focus on delivering scalable, high-quality solutions. Strong understanding of model evaluation metrics and uncertainty quantification Expert in Python preferred, R also accepted Statistical analysis skills Experience with modelling on GPU architectures Version control in Git Requirements Ph.D. in oceanography or atmospheric science, that makes heavy use of data science, applied mathematics, or a related field; or Master s with 3+ years of relevant experience. Key Responsibilities Contribute to pioneering storm surge research and model development in a framework where machine learning and numerical modeling are the basis of the storm surge modeling. Develop process improvement to optimize model performance Develop and maintain codebase, apply version control (e.g. Git) best practices

Position Opening For AI/ML Developer Experience: 1+ Year Location: Ahmedabad Minimum Required Skills as below 1+ years of experience in Machine Learning and Data Science projects. Hands-on experience with Python and ML libraries (e.g., scikit-learn, pandas, NumPy). Understanding of supervised and unsupervised learning techniques. Experience with model development, evaluation, and deployment. Ability to work independently. APPLY NOW

Job Title: Computer Vision AI Architect Location: Remote Salary: Competitive Job Description: Quantaleap INC. is seeking a seasoned Computer Vision AI Architect to lead solutioning and proposal efforts for utility and grid inspection projects. The ideal candidate will have a strong background in image analysis, machine learning, and aerial, facility, or medical imaging use cases. This role involves working closely with presales teams and contributing to RFP responses through technical leadership and innovative vision solutions. Key Responsibilities: Architect and design AI-based computer vision solutions for utility and infrastructure inspections. Analyze aerial, static, and medical imagery for inspection, anomaly detection, and image comparison tasks. Collaborate with presales and proposal teams to provide technical solutioning for RFPs. Generate visual inspection reports and present actionable insights. Ensure solution feasibility and scalability for deployment across client environments. Work Indian business hours with some required overlap with PST time zone. Must-Have Skills: Expertise in Computer Vision, Image Processing, and Image Compariso n Proficiency in Machine Learning frameworks and model development Experience in Aerial, Facility, and Medical Imaging use cases Strong background in RFP solutioning and presales technical support Excellent communication and reporting skills

Locations : Hyderabad, Telangana, India Role ID 209546 Worker Type Regular Employee Studio/Department CTO - EA Digital Platform Work Model Hybrid Description Requirements Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen. Software Engineer II - AI/ML Engineer The EA Digital Platform (EADP) group is the core powering the global EA ecosystem. We provide the foundation for all of EA s incredible games and player experiences with high-level platforms like Cloud, Commerce, Data and AI, Gameplay Services, Identity and Social. By providing reusable capabilities that game teams can easily integrate into their work, we let them focus on making some of the best games in the world and creating meaningful relationships with our players. We re behind the curtain, making it all work together. Come power the future of play with us. The Challenge Ahead: We are looking for developers who want to work on a large-scale distributed data system that empowers EA Games to personalize player experience and engagement. Responsibilities You will help with designing, implementing and optimizing the infrastructure for AI model training and deployment platform You will help with integrating AI capabilities into existing software systems and applications You will develop tools and systems to monitor the performance of the platform in real-time, analyzing key metrics, and proactively identify and address any issues or opportunities for improvement. You will participate in code reviews to maintain code quality and ensure best practices You will help with feature and operation enhancement for platform under senior guidance You will help with improving the stability and observability of the platform Qualifications Bachelors degree or foreign degree equivalent in Computer Science, Electrical Engineering, or related field. 3+ years of experience with software development and model development Experience with a programming language such as Go, Java or Scala Experience with scripting languages such as bash, awk, python Experience with Scikit-Learn, Pandas, Matplotlib 3+ years of experience with Deep Learning frameworks like PyTorch, TensorFlow, CUDA Hands-on experience of any ML Platform (Sagemaker, Azure ML, GCP Vertex AI) Experience with cloud services and modern data technologies Experience with data streaming and processing systems About Electronic Arts We re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth. We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do. Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law. LinkedInID 1449 Back to Role List

Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them. Chart your own path and grow your career while helping more customers achieve financial freedom. Empower Yourself. This role supports Empower s data and AI strategy, with a focus on building Responsible AI capabilities. The Data Engineer will design and implement scalable, ethical, and secure data pipelines and infrastructure that underpin AI/ML systems, ensuring high-quality data flows into model development, testing, monitoring, and governance workflows. The candidate will work across cloud (AWS) and on-premises environments, contributing to the lifecycle of data used for Responsible AI tooling, including bias detection, model transparency, and compliance tracking. ESSENTIAL FUNCTIONS: Design, build, and maintain data pipelines that support model development, testing, and monitoring, with a focus on AI governance and traceability. Collaborate with cross-functional teams (including Data Scientists, ML Engineers, and Risk) to understand data needs for AI use cases. Integrate data quality, lineage, and metadata tracking into ETL pipelines to support Responsible AI workflows. Support ingestion and transformation of structured and unstructured data (including NLP datasets) for AI model training and evaluation. Design with compliance in mind: integrate secure handling of PII and support auditability in data flows. Participate in technical design discussions focused on enabling transparency, fairness, and explainability in data workflows. Troubleshoot and resolve performance and data quality issues in distributed AI pipelines. Contribute to reusable libraries or templates to support standardized data practices across AI projects. QUALIFICATIONS: Bachelor s Degree in Computer Science , Information Systems, or related field. 2-6 years of experience in data engineering, preferably in AI/ML environments. Strong Python and SQL skills with experience in data pipeline orchestration (e.g., Airflow, Step Functions). Experience with Big Data frameworks (e.g., Spark, Hadoop) and streaming data platforms (e.g., Kafka). Experience working in AWS environments with services like S3, Glue, Redshift, SageMaker, and Lake Formation. Familiarity with machine learning workflows and data requirements (e.g., training/test splits, data versioning, feature stores). Experience integrating data validation, data lineage, or metadata tools (e.g., Great Expectations, Apache Atlas, Amundsen). Understanding of Responsible AI principles and experience supporting data aspects of fairness, bias, explainability, or model monitoring is a strong plus. Experience with JIRA and Agile methodologies. Experience in financial services or other highly regulated environments preferred. This job description is not intended to be an exhaustive list of all duties, responsibilities and qualifications of the job. The employer has the right to revise this job description at any time. You will be evaluated in part based on your performance of the responsibilities and/or tasks listed in this job description. You may be required perform other duties that are not included on this job description. The job description is not a contract for employment, and either you or the employer may terminate employment at any time, for any reason. We are an equal opportunity employer with a commitment to diversity. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to age, race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.

hands-on Analytics experience with 2+ years of experience. hands-on experience with one or more data analytics tools including Python, R, SAS, and SQL, SPARK Good understanding of credit card industry, financial Proficiency in Tableau is a plus

Job Title- Name List Screening and Transaction Screening Model Strats, AS Location- Bangalore, India Role Description Group Strategic Analytics (GSA) is part of Group Chief Operation Office (COO) which acts as the bridge between the Banks business and infrastructure functions to help deliver the efficiency, control, and transformation goals of the Bank. You will work within the Global Strategic Analytics Team as part of a global model strategy and deployment of Name List Screening and Transaction Screening. To be successful in that role, you will be familiar with the most recent data science methodologies and have a delivery-centric attitude, strong analytical skills, and a detail-oriented approach to breaking down complex matters into more understandable details. The purpose of Name List Screening and Transaction Screening is to identify and investigate unusual customer names and transactions and behavior, to understand if that activity is considered suspicious from a financial crime perspective, and to report that activity to the government. You will be responsible for helping to implement and maintain the models for Name List Screening and Transaction Screening to ensure that all relevant criminal risks, typologies, products, and services are properly monitored. We are looking for a high-performing Associate in financial crime model development, tuning, and analytics to support the global strategy for screening systems across Name List Screening (NLS) and Transaction Screening (TS). This role offers the opportunity to work on key model initiatives within a cross-regional team and contribute directly to the banks risk mitigation efforts against financial crime. You will support model tuning and development efforts, support regulatory deliverables, and help collaborate with cross-functional teams including Compliance, Data Engineering, and Technology. What well offer you As part of our flexible scheme, here are just some of the benefits that youll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your key responsibilities Support the design and implementation of the model framework for name and transaction screening including coverage, data, model development and optimisation. Support key data initiatives, including but not limited to, data lineage, data quality controls, and data quality issues management. Document model logic and liaise with Compliance and Model Risk Management teams to ensure screening systems and scenarios adhere to all model governance standards Participate in research projects on innovative solutions to make detection models more pro-active Assist in model testing, calibration and performance monitoring. Ensure detailed metrics & reporting are developed to provide transparency and maintain effectiveness of name and transaction screening models. Support all examinations and reviews performed by regulators, monitors, and internal audit Your skills and experience Advanced degree (Masters or PhD) in a quantitative discipline (Mathematics, Computer Science, Data Science, Physics or Statistics) 1–3 years experience in data analytics or model development (internships included). Proficiency in designing, implementing (python, spark, cloud environments) and deploying quantitative models in a large financial institution, preferably in Front Office. Hands-on approach needed. Experience utilizing Machine Learning and Artificial Intelligence Experience with data and the ability to clearly articulate data requirements as they relate to NLS and TS, including comprehensiveness, quality, accuracy and integrity Knowledge of the bank’s products and services, including those related to corporate banking, investment banking, private banking, and asset management How we’ll support you Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs About us and our teams Please visit our company website for further information https://www.db.com/company/company.htm

Management Level: Ind & Func AI Decision Science Consultant Location: Gurgaon, Mumbai, Bangalore Must-have skills: Risk Analytics, Model Development, Validation, and Auditing, Performance Evaluation, Monitoring, Governance, Statistical Techniques:Linear Regression, Logistic Regression, GLM, GBM, XGBoost, Time Series (ARMA/ARIMA), Programming Languages:SAS, R, Python, Spark, Scala, Tools:Tableau, PowerBI, Regulatory Knowledge:Basel/CCAR/DFAST/CECL/IFRS9, Risk Reporting and Dashboard Solutions Good to have skills: Advanced Data Science Techniques, AML, Operational Risk Modelling, Cloud Platform Experience (AWS/Azure/GCP), Machine Learning Interpretability and Bias Algorithms Job Summary We are seeking a highly skilled Ind & Func AI Decision Science Consultant to join the Accenture Strategy & Consulting team in the Global Network Data & AI practice. You will be responsible for risk model development, validation, and auditing activities, ensuring performance evaluation, monitoring, governance, and documentation. This role offers opportunities to work with top financial clients globally, utilizing cutting-edge technologies to drive business capabilities and foster innovation. Roles & Responsibilities: Engagement Execution Work independently/with minimal supervision in client engagements that may involve model development, validation, governance, strategy, transformation, implementation, and end-to-end delivery of risk solutions for Accentures clients. Ability to manage workstreams of small projects, overseeing the quality of deliverables for junior team members. Demonstrated ability to manage day-to-day interactions with client stakeholders. Practice Enablement Guide junior team members. Support development of the practice by driving innovations and initiatives. Develop thought leadership and disseminate information around current and emerging trends in Risk. Professional & Technical Skills: 2-6 years of relevant Risk Analytics experience at one or more Financial Services firms or Professional Services/Risk Advisory with significant exposure to Credit Risk: PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting, Revenue Forecasting Models, IFRS9/CECL Loss Forecasting across Retail and Commercial portfolios. Credit Acquisition/Behavior: Modeling, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios. Regulatory Capital and Economic Capital Models Liquidity Risk: Liquidity Models, Stress Testing Models, Basel Liquidity Reporting Standards Anti-Money Laundering (AML): AML Scenarios/Alerts, Network Analysis Operational Risk: AMA Modeling, Operational Risk Reporting Modeling Techniques: Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time Series (ARMA/ARIMA), ML Interpretability and Bias Algorithms Programming Languages & Tools: SAS, R, Python, Spark, Scala, Tableau, QlikView, PowerBI, SAS VA Strong understanding of Risk functions and their application in client discussions and project implementation. Additional Information: Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities. Industry Certifications:FRM, PRM, CFA preferred. Excellent Communication and Interpersonal Skills. About Our Company | Accenture Qualification Experience: Minimum 2-6 years of relevant Risk Analytics experience, Exposure to Financial Services firms or Professional Services/Risk Advisory Educational Qualification: Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities, Industry certifications such as FRM, PRM, CFA preferred

Job Title Ind & Func AI Decision Science Analyst - S&C GN Management Level :11 - Analyst Location:Gurgaon Must have skills: Generative AI, Machine Learning, Large Language Models (LLMs), Python, SQL Good to have skills:Spark, Cloud Platforms (AWS, Azure, GCP), NLP, Computer Vision Job Summary : As an AI Decision Science Analyst, you will play a key role in designing, building, and deploying advanced AI models and solutions to address business challenges across various industries. You will leverage Generative AI, Machine Learning, and Large Language Models (LLMs) to drive innovation and deliver impactful insights for clients. Your work will involve collaborating with cross-functional teams, and contributing to the development of advanced analytics capabilities. Roles & Responsibilities: Leverage Advanced Data Science Techniques Develop solutions using Generative AI, Machine Learning, and Large Language Models (LLMs). Define data requirements, clean, aggregate, analyze, and interpret data while conducting data quality assessments. Develop and Implement AI Models Build and deploy AI models and Generative AI applications. Train and fine-tune LLMs using large-scale datasets to optimize performance and accuracy. Evaluate model performance and implement iterative improvements. Solution Integration and Deployment Collaborate to integrate AI solutions into end-to-end workflows, ensuring scalability. Utilize cloud platforms like AWS, Azure, or GCP for model development and deployment. Innovation and Knowledge Sharing Stay updated on advancements in AI and Data Science, exploring innovative techniques and frameworks. Document methodologies and findings for effective knowledge sharing. Professional & Technical Skills: - Must To Have Skills: Proficiency in Generative AI, Machine Learning, LLMs, Python, SQL. Spark, Cloud platforms (AWS, Azure, GCP), NLP, Computer Vision. Experience in developing and AI/ML models. Additional Information: - The ideal candidate will possess a strong educational background in computer science or a related field, along with a proven track record of delivering impactful solutions using data science and analytics. This position is based at our Gurugram office. About Our Company | Accenture Qualification Experience: Minimum 1+ years of experience in Data Science, preferably within a consulting environment Educational Qualification: Bachelors or Masters degree (BE/BTech/MBA) in Statistics, Computer Science, Mathematics, or related disciplines with an excellent academic record

Management Level :07- I&F Decision Sci Practitioner Manager Location :Mumbai Must-have skills :Risk Analytics, Model Development, Validation, and Auditing, Performance Evaluation, Monitoring, Governance, Statistical Techniques:Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Programming Languages:SAS, R, Python, Spark, Scala, Tools:Tableau, QlikView, PowerBI, SAS VA, Regulatory Knowledge:Basel/CCAR/DFAST/CECL/IFRS9, Risk Reporting and Dashboard Solutions Good to have skills :Advanced Data Science Techniques, AML, Operational Risk Modelling, Cloud Platform Experience (AWS/Azure/GCP), Machine Learning Interpretability and Bias Algorithms Job Summary We are seeking a highly skilled I&F Decision Sci Practitioner Manager to join the Accenture Strategy & Consulting team in the Global Network Data & AI practice. You will be responsible for leading risk model development, validation, and auditing activities, ensuring performance evaluation, monitoring, governance, and documentation. This role also provides opportunities to work with top financial clients globally, utilizing cutting-edge technologies to drive business capabilities and foster innovation. Roles & Responsibilities: Engagement Execution Lead the team in the development, validation, governance, strategy, transformation, implementation, and end-to-end delivery of risk solutions for clients. Manage workstreams for large and small projects, overseeing the quality of deliverables for junior team members. Develop and frame Proof of Concept for key clients where applicable. Practice Enablement Mentor, guide, and counsel analysts and consultants. Support the development of the practice by driving innovations and initiatives. Support efforts of sales team to identify and win potential opportunities by assisting with RFPs, RFI. Assist in designing POVs, GTM collateral. Professional & Technical Skills: 7-12 years of relevant Risk Analytics experience at one or more Financial Services firms or Professional Services / Risk Advisory with significant exposure to Credit Risk :PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting, Revenue Forecasting Models, IFRS9/CECL Loss Forecasting across Retail and Commercial portfolios. Credit Acquisition/Behavior :Modeling, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios. Regulatory Capital and Economic Capital Models Liquidity Risk :Liquidity Models, Stress Testing Models, Basel Liquidity Reporting Standards Anti-Money Laundering (AML) :AML Scenarios/Alerts, Network Analysis Operational Risk :AMA Modeling, Operational Risk Reporting Modeling Techniques :Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time Series (ARMA/ARIMA), ML Interpretability and Bias Algorithms Programming Languages & Tools :SAS, R, Python, Spark, Scala, Tableau, QlikView, PowerBI, SAS VA Strong understanding of Risk functions and their application in client discussions and project implementation. Additional Information: Masters Degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities Industry Certifications :FRM, PRM, CFA preferred Excellent Communication and Interpersonal Skills About Our Company | Accenture Qualification Experience :Minimum 7-12 years of relevant Risk Analytics experience, Exposure to Financial Services firms or Professional Services/Risk Advisory Educational Qualification :Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities, Industry certifications such as FRM, PRM, CFA preferred

Job Summary: Job Function: Model Development Associate Consultant/Consultant, is a key member of the Risk Analytics and Data Service Team and Responsible for acting as an individual contributor in the development and maintenance of high quality risk analytics. Resolves complex issues in Credit Risk/ PPNR modelling and measuring risk, enhancement in Credit Risk/ PPNR methodologies or other aspects of risk measurement. Job title: Associate Consultant/Consultant Location: Bangalore Experience: 4-8 years of relevant experience Major Duties Responsible for Development of CCAR models (PD/EAD/LGD) , CECL models (PD/EAD/LGD) and Basel models (PD/EAD/LGD). Also for PPNR model development for Non-Interest Income, Net Interest Income, Expense, Deposit, Balance models. Ensures regular production of analytical work.. Collaborates with regulators, Audit Services, and other independent reviewers. Evaluates existing framework in relation to corporate objectives and industry leading practices. Assesses development needs and manages process to achieve desired future state. Supports stress testing, capital quantification and/or internal capital allocation methodologies. Ensures that modelling approaches meet both internal corporate needs and regulatory requirements related to prevailing regulatory guidance. Provides technical/theoretical inputs to resolve risk issues and enhance overall risk framework. Works with other risk or business unit teams to ensure that risk management policies/processes and quantitative modelling approaches are consistent. Operates independently; has knowledge of banking balance sheets and income statements. Conducts analysis, independently ensuring accuracy and completeness. Responsible for interaction with different committees and/or senior management. Qualification: Master in Statistics/ Economics/Mathematics/advanced degree in quant area Or B.tech. From tier 1 college with MBA in related field Skills Required: Strong BASEL, CCAR and DFAST, SR-11/7 understanding. Strong regulatory understanding 2+ years of hands on model building experience in Credit Risk / PPNR Strong conceptual and technical knowledge of risk concepts and quantitative modelling techniques including familiarity with statistical concepts used in stress testing Strong in quantitative skills - experience in model validation a plus Experience in R, SAS, Matlab, advanced Excel techniques and VBA programming. SAS is preferred Strong Experience in building linear regression models, Nonlinear regression, time series modeling (ARIMA, AR, VAR, MA ) and stochastic process Strong organizational and interpersonal skills Excellent verbal and written communication skills (English) Experience of working in a multi-cultural and global environment Related Industry qualification (e.g., CFA, FRM) a plus

Job Summary This job will oversee the strategic direction and execution of machine learning projects. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences. Your Way to Impact As a Sr. Staff Machine Learning Engineer, you ll be instrumental in scaling PayPal s AI capabilities through advanced fine-tuning and foundational model development. Your work will directly enhance how we serve our customers with intelligent, adaptive, and personalized experiences. From conversational agents to smart automation, the models you build will be embedded across PayPal s ecosystem, impacting millions of users globally. Meet Our Team You ll be part of the Applied Intelligence organization, working alongside product, platform, and infrastructure teams. We power next-gen experiences through a unified AI stack accelerating time-to-value for internal users and building intuitive solutions for consumers and merchants. You ll be joining a team that values experimentation, scalability, and operational excellence in AI systems. Job Description Your Day to Day Fine-tune and optimize advanced machine learning and foundational models. Build reusable training pipelines and inference systems for production-grade deployment. Collaborate with cross-functional teams to integrate models into product experiences and backend workflows. Continuously monitor, test, and improve model performance in live environments. Mentor junior engineers and contribute to team-wide knowledge sharing. Participate in internal forums, technical design reviews, and possibly external publications. What You Need to Bring Bachelor s degree or equivalent, with at least 12-15 years of relevant experience. Strong hands-on experience with ML frameworks like PyTorch, TensorFlow, or Hugging Face. Experience fine-tuning large models (e.g., LLMs, vision-language models) using SFT, LoRA, RLHF, etc. Proven experience deploying ML models on cloud platforms such as AWS, GCP, or Azure. Deep knowledge of MLOps practices and tooling (e.g., model registries, CI/CD for ML). Preferred Qualification Subsidiary PayPal Travel Percent 0 For the majority of employees, PayPals balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https//www.paypalbenefits.com . Who We Are Click Here to learn more about our culture and community. Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. . Belonging at PayPal Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community . We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don t hesitate to apply.