217 Model Development Jobs - Page 9

The Team: As a Senior Lead Machine Learning Engineer of the Document Platforms and AI Team, you will play a critical role in building the next generation of data extraction tools, working on cutting-edge ML-powered products and capabilities that power natural language understanding, information retrieval, and data sourcing solutions for the Enterprise Data Organization and our clients. This is an exciting opportunity to shape the future of data transformation and see your work make a real difference, all while having fun in a collaborative and engaging environment. You'll spearhead the development and deployment of production-ready AI products and pipelines, leading by example and mentoring a talented team. This role demands a deep understanding of machine learning principles, hands-on experience with relevant technologies, and the ability to inspire and guide others. You'll be at the forefront of a rapidly evolving field, learning and growing alongside some of the brightest minds in the industry. If you're passionate about AI, driven to make an impact, and thrive in a dynamic and supportive workplace, we encourage you to join us! The Impact: The Document Platforms and AI team has already delivered breakthrough products and significant business value over the last 3 years. In this role you will be developing our next generation of new products while enhancing existing ones aiming at solving high-impact business problems. Whats in it for you: Be a part of a global company and build solutions at enterprise scale Collaborate with a highly skilled and technically strong team Contribute to solving high complexity, high impact problems Responsibilities: Build production ready data acquisition and transformation pipelines from ideation to deployment. Being a hands-on problem solver and developer helping to extend and manage the data platforms. Apply best practices in data modeling and building ETL pipelines (streaming and batch) using cloud-native solutions Technical leadership: Drive the technical vision and architecture for the extraction project, making key decisions about model selection, infrastructure, and deployment strategies. Model development: Design, develop, and evaluate state-of-the-art machine learning models for information extraction, leveraging techniques from NLP, computer vision (if applicable), and other relevant domains. Data preprocessing and feature engineering: Develop robust pipelines for data cleaning, preprocessing, and feature engineering to prepare data for model training. Model training and evaluation: Train, tune, and evaluate machine learning models, ensuring high accuracy, efficiency, and scalability. Deployment and monitoring: Deploy and maintain machine learning models in a production environment, monitoring their performance and ensuring their reliability. Research and innovation: Stay up-to-date with the latest advancements in machine learning and NLP, and explore new techniques and technologies to improve the extraction process. Collaboration: Work closely with product managers, data scientists, and other engineers to understand project requirements and deliver effective solutions. Code quality and best practices: Ensure high code quality and adherence to best practices for software development. Communication: Effectively communicate technical concepts and project updates to both technical and non-technical audiences. What Were Looking For: 8-10 years of professional software work experience, with a strong focus on Machine Learning, Natural Language Processing (NLP) for information extraction and MLOps Expertise in Python and related NLP libraries (e.g., spaCy, NLTK, Transformers, Hugging Face) Experience with Apache Spark or other distributed computing frameworks for large-scale data processing. AWS/GCP Cloud expertise, particularly in deploying and scaling ML pipelines for NLP tasks. Solid understanding of the Machine Learning model lifecycle, including data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring, specifically for information extraction models . Experience with CI/CD pipelines for ML models, including automated testing and deployment. Docker & Kubernetes experience for containerization and orchestration. OOP Design patterns, Test-Driven Development and Enterprise System design SQL (any variant, bonus if this is a big data variant) Linux OS (e.g. bash toolset and other utilities) Version control system experience with Git, GitHub, or Azure DevOps. Excellent Problem-solving, Code Review and Debugging skills Software craftsmanship, adherence to Agile principles and taking pride in writing good code Techniques to communicate change to non-technical people Nice to have Core Java 17+, preferably Java 21+, and associated toolchain Apache Avro Apache Kafka Other JVM based languages - e.g. Kotlin, Scala C# - in particular .NET Core

Job Description Job Overview: We are seeking an experienced Lead Model Developer with exceptional expertise in credit risk modeling, especially the wholesale portfolio (banks, corporate, specialized lending, real estate, non-banking). The ideal candidate will bring deep domain knowledge and advanced technical skills to drive sophisticated credit risk modeling initiatives across wholesale portfolios. Position Details: Location: Pan India Experience Level: 10+ years Employment Type: Full-time Key Responsibilities: Lead end-to-end development of advanced credit risk models, including PD, EAD, LGD models compliant to IRB Standards Conduct comprehensive data preparation, preprocessing using tools including SAS, Python, R, and SQL Design, build, calibrate and implement robust credit risk models across wholesale portfolios with rigorous User Acceptance Testing (UAT) Collaborate with cross-functional stakeholders to analyze, interpret, and communicate complex model results and insights Develop comprehensive technical documentation including: Model documentation Business Requirements Documents (BRD) Validation reports Regulatory compliance documentation Drive continuous model improvement through: Identifying optimization opportunities; Implementing advanced modeling techniques; Enhancing model performance and predictive accuracy Provide mentorship and technical guidance to junior team members, fostering a culture of knowledge sharing and professional development Required Qualifications: 10+ years of hands-on experience in credit risk model development Proven expertise in modeling across wholesale/LDP credit portfolios Advanced proficiency in: SAS, Python, R, SQL Strong knowledge of capital models (IRB approach) Good to have a understanding of IFRS9 and CECL regulatory frameworks Exceptional analytical and problem-solving skills Excellent written and verbal communication abilities Preferred Qualifications: Advanced degree in Statistics, Mathematics, Economics, or related field Professional certifications in risk management or financial modeling Experience with machine learning and advanced statistical modeling techniques Knowledge of Basel regulatory requirements Technical Skills: Model Development: PD, LGD, EAD Programming: SAS, Python, R, SQL Regulatory Knowledge: IRB (must), Good to have (IFRS9, CECL) Data Preprocessing / Statistical Modeling / Machine Learning Techniques

Key Responsibilities: Leverage traditional machine learning techniques (decision trees, random forests, SVM, logistic regression) to build predictive models. Analyze complex datasets to identify key trends and provide data-driven insights for business decisions. Partner with cross-functional teams to understand business needs and translate them into effective ML solutions. Rigorously evaluate and optimize models for accuracy and real-world performance. Apply statistical and mathematical principles to enhance analytical outcomes. Communicate findings and model insights to both technical and non-technical stakeholders. Desired Skills and Qualifications: Deep understanding of traditional machine learning algorithms (decision trees, clustering, Naive Bayes, SVM, etc.). Strong proficiency in mathematics and statistics (linear algebra, probability, statistical inference). Proven ability to translate business problems into analytical frameworks and actionable insights. Expertise in data processing, cleaning, and feature engineering using Python (pandas, NumPy). Hands-on experience building and deploying ML models using Python and libraries like scikit-learn. Excellent analytical, problem-solving, and critical thinking skills. Strong communication and collaboration skills to effectively convey technical results. Familiarity with ML tools and frameworks (Scikit-learn, XGBoost, LightGBM). Experience with model evaluation, validation, and optimization techniques. Business acumen and the ability to apply ML to solve real-world business challenges. Preferred Qualifications: Bachelors or Masters degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field. 3+ years of experience as a Data Scientist with a focus on machine learning. Demonstrated experience in driving business decisions through data analysis and modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for data science workflows.

Skill required: Delivery - Credit Risk Modeling Designation: I&F Decision Sci Practitioner Sr Analyst Qualifications: Any Graduation Years of Experience: 5 to 8 years What would you do? Data & AICredit risk modelling refers to the use of financial models to estimate losses a firm might suffer in the event of a borrower s default. What are we looking for? Primary Skills: Banking, Financial Services Credit Risk Model Development Market Risk Modelling Financial Regulations Quantitative AnalysisSecondary Skills: SQL SAS Python R Tableau VBA Qlik Sense Snowflake MatillionSoft Skills: Adaptable and flexible Commitment to quality Ability to work well in a team Agility for quick learning Written and verbal communication Roles and Responsibilities: In this role you are required to do analysis and solving of increasingly complex problems Your day-to-day interactions are with peers within Accenture You are likely to have some interaction with clients and/or Accenture management You will be given minimal instruction on daily work/tasks and a moderate level of instruction on new assignments Decisions that are made by you impact your own work and may impact the work of others In this role you would be an individual contributor and/or oversee a small work effort and/or team Qualification Any Graduation

Skill required: Delivery - Credit Risk Modeling Designation: I&F Decision Sci Practitioner Specialist Qualifications: Any Graduation Years of Experience: 7 to 11 years What would you do? Data & AICredit risk modelling refers to the use of financial models to estimate losses a firm might suffer in the event of a borrower s default. What are we looking for? Primary Skills: Banking, Financial Services Credit Risk Model Development Market Risk Modelling Financial Regulations Quantitative AnalysisSecondary Skills: SQL SAS Python R Tableau VBA Qlik Sense Snowflake MatillionSoft Skills: Adaptable and flexible Commitment to quality Ability to work well in a team Result Oriented Problem Solving Skills Roles and Responsibilities: In this role you are required to do analysis and solving of moderately complex problems May create new solutions, leveraging and, where needed, adapting existing methods and procedures The person would require understanding of the strategic direction set by senior management as it relates to team goals Primary upward interaction is with direct supervisor May interact with peers and/or management levels at a client and/or within Accenture Guidance would be provided when determining methods and procedures on new assignments Decisions made by you will often impact the team in which they reside Individual would manage small teams and/or work efforts (if in an individual contributor role) at a client or within Accenture Qualification Any Graduation

Min exp 3 years in pd. lgd MODELS. IFRS9/ IRB model validation/ development/monitoring exp mandatory Package upto 55 lpa Depends on exp Required Candidate profile Bangalore/Noida location Please send cv's on supreetbakshi@imaginators.co or Call on 7042331616 Please send cv's on email only

Sony is looking for a Deep Learning engineer who has strong knowledge and experience in design and development of Deep learning models according to business objectives. In this role, the candidate must analyse the requirements, prepare design and implement Deep Learning solutions. This requires a sound understanding of ML and Deep Learning fundamentals, libraries and frameworks, end-to-end ML development pipeline. Literature survey of SOTA models as per business requirements and AS-Is reproduction of Deep Learning models. Design and development of CNN models according to the business objective, along with metrics to track their progress. Optimize the CNN models in terms of trainable parameters and MAC operations to meet the target platform. Debug the intermediate as well as final layer output of trained model using various explainable AI methods. Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world and Evaluation approaches for model development Training models and tuning their hyperparameters Analysing the errors of the model and designing strategies to overcome them Skills set required: Advanced Python Programming Image processing using OpenCV. Keras, TensorFlow Good to have skills: Deep knowledge of math, probability, statistics and algorithms CNN Development Advanced OOPS concepts Roles and Responsibilities 1. Analyse customer requirements Design and Implement features requested by customer Verify, finetune solution and model and artefacts Validation of quality as per requirements 2. Customer communication 3. Also mentor junior members and ensure quality of deliverables in the project

Immediate opening for "Computer Vision AI Architect" Location :- Remote Experience :- 15 to 23 yrs 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 or facility inspection 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 and static 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 Comparison Proficiency in Machine Learning frameworks and model development Experience in Aerial and Facility Inspection use cases Strong background in RFP solutioning and presales technical support Excellent communication and reporting skills Interested can share their updated resume to anitha.mudaliyar@quantaleap.com

Roles and Responsibilities Develop credit risk or fraud risk models using Python, 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 5+ years of experience in Credit Risk Modelling/ Fraud Modeling or related field. Strong expertise in PD, LGD Model Development ,Basel II/III regulations, CECL/CCAR requirements under IFRS9 framework. Proficiency in programming languages such as Python/R/SAS/SQL; strong understanding of machine learning algorithms an added advantage.

About The Role : In Scope of Position based Promotions (INTERNAL only) Job TitleProduct Tagging Validation Specialist Corporate TitleAVP LocationMumbai, India Role Description This role in Product Tagging Validation team is responsible for validating the product name assigned to trades across all asset classes globally. The product name is used to determine model appropriateness and classify trades for various reporting processes (such as Regulatory Reporting, trader mandates, etc.). As part of Valuations Control (IPV) team this role ensures DB approved valuation models are used for pricing/risk generation for a particular product. This role interacts regularly with the Front Office (Strats and Trading), Global Model Validation Group, Pricing Analytics, Group Audit and Global Technology. In addition to tag validation, the team is also responsible for calculating FV Reserves due to Model limitation/deficiency and provide transparency on IFRS lvelling. This team also assists the Front Office with the remediation of tagging exceptions. The ultimate goal is to establish an efficient, accurate, up-front control over the tagging of trades such that error detection and subsequent remediation are not required. Therefore, there is a substantial amount of project work in addition to a business as usual process. What we'll 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 As a product specialist you will be responsible for: Analysing products and trade booking to determine the logic required to automatically determine the product type and features. Ensure dbapproved product-model combinations used, identify exceptions and work with stakeholders towards remediation. Engage with IPV business aligned teams to provide them visibility on exceptions and calculate model limitation/deficiency reserves and/or appropriate IFRS levellings. Enhancing the BAU process by improving validation efficiency and accuracy and ultimately converting it from a monthly into a daily process. Working with developers to implement validation logic to ensure it is consistently applied and sufficiently documented. Working with Trading and Strats to remediate product tagging and definition issues to improve the Model Risk Control environment. Managing operational risk by ensuring processes are documented and staff are cross-trained. Developing your technical expertise to ensure you have the knowledge to face-off against technical experts in divisions outside of Business Finance. Producing presentations and communicating progress to Auditors and Regulators. Your skills and experience Previous experience working with banking products and understanding how theyre booked Experience in dealing with Front Office business leaders Pricing and modeling of derivative products Knowledge of front-to-back architecture of Investment Banks Programming experience in SQL, C++, Python an advantage Education/ Qualifications/Character Degree 2.1 or above (or equivalent) ACA, CIMA, CFA, Relevant Masters Degree Strong derivatives product knowledge Control focused, deadline orientated, team player with high attention to detail People Management The behaviours provided below should be adopted by all Deutsche Bank employees in relation to their development and management of others. Supports the development of an environment where people management and development is the number one priority. Coaches direct reports and others in the organisation, as appropriate Actively supports the business strategy, plans and values, contributing to the achievement of a high performance culture Takes ownership for own career management, seeking opportunities for continuous development of personal capability and improved performance contribution Acts as a role model for new employees, providing help and support to facilitate early integration and assimilation of their new environment Supports tough people decisions to ensure people performance is aligned with organisation imperatives and needs. Addresses individual performance issues, where necessary, to drive for high performance 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 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.

About The Role : In Scope of Position based Promotions (INTERNAL only) Job Title- MoRM Risk and CapitalModel Validatior, AS Location- Mumbai, India Role Description Model Risk Managements mission is to manage, independently and actively, model risk globally in line with the bank's risk appetite with responsibility for: Performing robust independent model validation; Ensuring early and proactive identification of Model Risks; Designing and recommending Model Risk Appetite; Effectively managing and mitigating Model Risks; Designing and implementing a strong Model Risk Management and governance framework; Creating bank-wide Model Risk related policies. What we'll 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 You will be responsible for the timely and high-quality delivery of validation reports for all Risk and Capital Models developed for Credit Risk. Develop and set state-of-the-art validation approaches and standards adhering to current and upcoming regulatory requirements. Ensure implementation of these standards in particular through review and pre-approval of validation reports. Present and defend work in internal committees. Pro-actively engage in management of Model Risk to assure Model Risk requirements. Additionally, support, coach and guide new and established team members and closely engage with stakeholders from Risk, Finance, IT and Business. Your skills and experience Masters in Statistics / Mathematics / Quantitative Economics / Quantitative Finance or MBA Finance Professional experience 2-7 yrs in quantitative Credit risk model development or validation is a requirement Perennial professional experience in financial risk management in general with a strong IT affinity Extensive knowledge with relevant statistical and other software packages and programming languages (e.g. SAS, R, SQL, Python) Pronounced conceptual and analytical skills and excellent project management Proven ability to solve problems independently, to show flexibility and to act proactively Business fluent written and verbal skills in English 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

Job Description: We are looking for a talented and motivated AI/ML & GenAI Engineer with an experience of 8 - 12 years of total IT experience and not less than 5 years of exposure to real-time AI based projects (Any academic or professionally accreditations in the AI space will be extremely nice to have) to join our innovative team and drive the development of intelligent solutions that solve complex problems. In this role, you will design, build, and deploy machine learning models and AI systems that integrate seamlessly into our products and services. You will collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to identify opportunities where AI/ML & GenAI solutions can deliver value. This role offers the chance to work on cutting-edge technologies, develop scalable algorithms, and contribute to shaping the future of AI-powered solutions. Data Preparation & OCR Integration: Clean and preprocess raw data, implement like AWS Textract for high accuracy document extraction, and seamlessly integrate outputs into downstream ETL pipelines. NLP Development: Build, fine tune, and deploy NLP models for domain specific tasks such as proposal analysis and financial text processing. AI/ML Model Development: Architect, train, and productionize machine learning models to assess profitability, classify proposals, and deliver automated recommendations. Generative AI & LLM Engineering: Design and implement retrieval augmented generation (RAG) pipelines, integrate large language models (e. g. , AWS Bedrock, LLaMA) with frameworks like LangChain, and refine prompt engineering strategies for precise, domain specific content generation. Deployment & Monitoring: Deploy AI/ML and Generative AI solutions on platforms like AWS SageMaker, establish real time monitoring and alerting, and ensure horizontal scalability. System Integration & Optimization: Embed AI/ML components into existing workflows, optimize for low latency and resource efficiency, and maintain robust error handling. Research & Experimentation: Stay abreast of emerging AI/ML and Generative AI innovations, conduct experiments with state of the art algorithms, and perform A/B testing to validate model performance. Recruitment fraud is a scheme in which fictitious job opportunities are offered to job seekers typically through online services, such as false websites, or through unsolicited emails claiming to be from the company. These emails may request recipients to provide personal information or to make payments as part of their illegitimate recruiting process. DXC does not make offers of employment via social media networks and DXC never asks for any money or payments from applicants at any point in the recruitment process, nor ask a job seeker to purchase IT or other equipment on our behalf. More information on employment scams is available here .

Due to a healthy pipeline of projects and opportunities, we are seeking an experienced transport modeller and data analyst with a passion for sustainable transport to join the team. Experience in transport modelling both model development and application, use of big data and an interest in decarbonisation, transport appraisal and the automation of modelling is important . We are seeking an experienced transport professional, specialising in strategic transport modelling (Saturn & VISUM), with a background supporting modelling for Local Plans, transport strategies and business cases. Skills in data science including using Python, SQL, GIS and working with big data would be desireable.

Who we are looking for: Monk is leading the way in AI-driven innovation with its advanced damage detection technology for vehicles, enabling seamless integration into web and native applications via APIs. Our machine learning expertise is trusted by global leaders like our parent company ACV Auctions (USA), CAT Logistics (Europ Getaround (France), Autobiz (Europe), and Hgreg (Canad We are looking for a Machine Learning Scientist in Computer Vision who thrives on taking ownership, delivering impactful results, and driving innovation. If you're someone who can align with business needs, ensure timely delivery, and elevate the team's capabilities, we’d love to have you on board. This role is your opportunity to lead game-changing projects, create tangible value, and shape the future of AI technology in the automotive space. What you will do: Own the end-to-end development of machine learning models and datasets to solve critical business challenges and meet product needs. Drive innovation by continuously tracking and integrating state-of-the-art advancements of computer vision and deep learning into Monk’s AI solutions Identify and solve key business problems with data-driven, actionable insights. Deliver high-impact results through meticulous planning, rigorous testing, and smooth deployment of machine learning solutions. Mentor and support junior team members, cultivating a culture of excellence and collaboration. Machine Learning Scientist CV Collaborate with product, business, and technical teams to align on priorities, estimate efforts, and adapt to feedback. Ensure long-term reliability and scalability through robust documentation and testing practices. Tech Stack Utilized: Languages: Python, SQL Libraries/Frameworks: PyTorch ecosystem, a touch of OpenCV and Scikit-learn Tools: Jupyter, DBT, Docker Infrastructure: GCP, Kubernetes, BigQuery Version Control: GitHub Background and Skills: Required Skills 5+ years of experience in computer vision, data science or related fields, wit a proven track record of delivering impactful results. Strong foundation in machine learning, computer science, statistical modeling, and data processing pipelines. Proficiency in Python and SQL for data manipulation and model development. Solid experience deploying machine learning models into production environments. A proactive approach to aligning with business needs and driving team-wide innovation. Strong communication skills to explain technical concepts to non-technical stakeholders. Fluent in English, enabling effective collaboration across global teams. Desired Background Master’s or Ph.D. in Data Science, Computer Science, or a related field Experience in B2B SaaS, automotive technology, or AI-driven startups. Knowledge of working with distributed teams across time zones. A proactive mindset, with the ability to work autonomously in fast-paced environments. #LI-RG1

Urgent Hiring for MNC for Analytics role, which includes- Model Development/Model Validation Data Analytics Data Manager/Data Modeler Risk Strategy/Analytics Market Risk/Credit Risk SAS/Python Exposure Kindly send your updated CV at jatin@smrd.in

What you will do Build end-to-end machine learning models to solve business problems in Marketing Perform feature engineering and support data engineering to build robust data pipelines on large marketing datasets from different sources Collaborate with ML Engineering to build ML Pipelines to Train, Test, Deploy, Serve and Monitor models, Tune Hyperparameters, detect model and data drift and resolve issues Present machine learning models outcomes, and help interpret model predictions to various stakeholders using standard data visualization tools Contribute to designing Experiments to prove hypothesis, and conduct A/B testing Write unit test cases, validation checks, technical documentation, and user stories as per requirements What you will need Must: Experience in all phases of machine learning lifecycle including model selection, training, and evaluation, feature engineering, tuning hyperparameters, and deployment Must: Knowledge of CI/CD, Github Actions, Docker Must: Hands-on experience with Python, Software development concepts (Object-oriented or Functional Programming) Must: Proficient in Tensorflow or PyTorch, Keras, Jupyter Notebooks, GitHub, and SQL Must: Experience with atleast one deep learning and/or Causal Inferencing Must: Experience working in cloud platforms like AWS, and Big data technologies Nice to have: Hands-on experience with A/B Test result analysis and Experimentation Nice to have: Worked with large marketing dataset in Digital Marketing, Google Analytics, Adobe Omniture, etc. Bonus: GenAI or Agentic AI experience Note - Please note that this role requires to work 3 days from office in Bangalore. Plz apply only if you are fine to work from office.

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: Master's 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 :Master’s 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