221 Model Development Jobs - Page 2

Role Purpose Anaplan, Anaplan Model Builder, Integrations and SQL Do 3+ years of Model development and business process architecting using EPM tools Strong expertise and deep understanding of multi-dimensional modeling Basic to intermediate knowledge of SQL Expert skills of Excel spreadsheet modeling, macros, pivot tables, formulas, charts etc. Strong understanding of data integration Self-motivated and ability to manage timelines across multiple projects. Strong interest in structured finance preferred. Deliver excellent customer service through effective diagnosis and troubleshooting of client queries Provide product support and resolution to clients by performing a question diagnosis while guiding users through step-by-step solutions Assist clients with navigating around product menus and facilitate better understanding of product features Troubleshoot all client queries in a user-friendly, courteous and professional manner Maintain logs and records of all customer queries as per the standard procedures and guidelines Accurately process and record all incoming call and email using the designated tracking software Offer alternative solutions to clients (where appropriate) with the objective of retaining customers and clients business Organize ideas and effectively communicate oral messages appropriate to listeners and situations Follow up and make scheduled call backs to customers to record feedback and ensure compliance to contract /SLAs Build capability to ensure operational excellence and maintain superior customer service levels of the existing account/client Undertake product trainings to stay current with product features, changes and updates Enroll in product specific and any other trainings per client requirements/recommendations Partner with team leaders to brainstorm and identify training themes and learning issues to better serve the client Update job knowledge by participating in self learning opportunities and maintaining personal networks Deliver NoPerformance ParameterMeasure1ProcessNo. of cases resolved per day, compliance to process and quality standards, meeting process level SLAs, Pulse score, Customer feedback2Self- ManagementProductivity, efficiency, absenteeism, Training Hours, No of technical training completed

Role & responsibilities Develop, support, and enhance statistical models to predict the risk of credit downgrade and default. Apply expertise in Fixed Income / Credit Risk, including Probability of Default (PD), Loss Given Default (LGD), and other credit risk measures. Analyse and interpret financial instruments, derivatives, and portfolio management principles to improve risk assessment. Utilize Python, SQL, and Excel to work on large datasets, extract insights, and automate data processing workflows. Develop automated processes and tools to improve efficiency and accuracy in data production and risk modelling. Lead Bottom-Up Data Production processes, ensuring effective planning, monitoring, and timely completion of deliverables. Collaborate with key stakeholders including Deal Teams, Execution, Technology, and Risk Reporting to enhance the Quant Credit Infrastructure. Utilize SQL to extract and manipulate data from large-scale databases, ensuring data integrity and accuracy. Manage and optimize project workflows using Asana/JIRA and other project management tools. Preferred candidate profile 5+ years of experience in a project/process management team within the finance domain. Strong knowledge of corporate accounting concepts and financial reporting. Solid understanding of credit risk concepts and downgrade risk assessment. Advanced proficiency in Microsoft Office (Excel, PowerPoint); VBA is a plus. Proven ability to implement Spreading Policy in corporate financials, particularly in SIP and Direct Lending. Strong organizational and analytical problem-solving skills. High attention to detail and persistence in ensuring data quality. Ability to work autonomously with minimal supervision. Intermediate/Advanced SQL skills for database management and data extraction. Python proficiency for automation and model development. Experience in project management tools like Asana, JIRA. Strong academic background with a business-related degree (MBA preferred) CFA certification is a plus.

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up . Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful. Overview about TII At Target, we have a timeless purpose and a proven strategy. And that hasnt happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Targets global team and has more than 4,000 team members supporting the companys global strategy and operations. Team Overview: Our Supply Chain Data Science team oversees the development of state-of-the-art mathematical techniques to help solve important problems for Targets Supply Chain e.g., identifying the optimal quantities and positioning of inventory across multiple channels and locations, planning for the right mix of inventory investments vs guest experience, digital order fulfillment planning, transportation resource planning, etc. As a Senior Data Scientist in Digital fulfilment space, you will have the opportunity to work with Product, Tech, and Business Partners to solve retail challenges at scale for our fulfillment network. Position Overview: As aSenior Data Scientist at Target, you will get an opportunity design,develop, deploy, and maintain data science models and tools. Youll work closely with applied data scientists, data analysts and business partners to continuously learn and understand evolving business needs. Youll also collaborate with engineers and data scientists onpeerteams to buildand productionizefulfillment solutions for our supply chain/logistics needs. Develop a strong understanding of business/ operational processes within Targets supply chain. Develop an in-depth understanding of the various systems and processes that influence digital order fulfillment speed & costs. Develop optimization-based solutions, approximate mathematical models (probabilistic/deterministic models) of real-world phenomena, predictive models and implement the same in real production systems with measurable impact. Analyze large datasets for insights leading to business process improvements or solution development. Develop and deploy modules for testing and validating multiple scenarios to evaluate the impact of various fulfillment strategies. Adopt modular architecture and good solution development practices to enhance the overall product performance and guide other team members. Produce clean, efficient code based on specifications. Coordinate the analysis, troubleshooting and resolution of issues in the models and software. About You: Must Have: We are looking for candidates who combine rigorous machine learning skills with a decent grasp of optimization and applied math. You should have: Bachelors/Masters/PhD in Computer Science, Mathematics, Statistics, Operations Research, or a related quantitative discipline. 4+ years of experience working across ML and optimization domains , ideally in dynamic, real-world problem spaces. Strong coding skills in Python and experience working with Spark or distributed data frameworks. Hands-on experience with ML modeling pipelines , from data ingestion and feature engineering to model development, evaluation, and deployment. Knowledge of OR techniques (e.g., LP/MIP) and how to integrate them with ML systems. Strong problem-solving skills with a track record of delivering solutions to complex, ambiguous business problems. Ability to independently own and drive projects end-to-end in a collaborative environment. Excellent communication skillsboth technical and strategicacross engineering and business teams. Preferred Experience: Experience with MLOps frameworks and practices (e.g., model versioning, CI/CD for ML, monitoring). Exposure to supply chain, logistics, or fulfillment optimization problems. Experience working in a production-scale environment with high data volume and business-critical pipelines. Ability to build solution/ models that operate at low latency. Know More here: Life at Target - https://india.target.com/ Benefits - https://india.target.com/life-at-target/workplace/benefits Culture- https://india.target.com/life-at-target/belonging

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful. Overview about TII: At Target, we have a timeless purpose and a proven strategy. And that hasnt happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Targets global team and has more than 4,000 team members supporting the companys global strategy and operations. Pyramid overview: A role with Target Techs Data Science team means the chance to develop and manage state of the art machine learning algorithms that use data at scale to automate and optimize decisions. Whether you join our Statistics, Optimization or Machine Learning teams, youll be challenged to harness Targets impressive data breadth to build the algorithms that power solutions our partners in in Stores, Supply Chain Optimization, and Network Planning rely on. Every Scientist on Targets Data Sciences team can expect modelling and data science, software/product development of highly performant code for performance, and to elevate Targets culture and apply retail domain knowledge. Team Overview: Our Stores Data Science team oversees the development of state-of-the-art mathematical techniques to solve key problems for Targets Stores, such as identifying optimal tasks prioritizing work and sequence work for our teams to meet the dynamic guest demands. The team leverage machine learning, operations research and simulation to help design the future of how our stores work. Position Overview: As aLead Data Scientist, youll influence by interacting with the Data Sciences team, Product teams, Scientist/Engineer individual contributors from other pillars, and business partners. You will perform within the scope of your role by defining solutions and beginning to identify problems to solve. You will contribute to Data Sciences and Targets culture by modeling and contributing to the ways we work. There are several ways to use your expertise in one or more of the following areasmachine learning, probability theory & statistics, optimization theory, Simulation, Econometrics, and machine learning. We will look to you to own design and implementation of an algorithmic solution (e.g., predictions, optimization or simulations), including data understanding, feature engineering, model development, validation and testing, and deployment to a production environment. Youll drive development of problem statements that capture the business considerations, define metrics/measurement to validate model performance, and drive feasibility study with data requirements and potential solutions approaches to be considered. Youll evaluate trade-offs of simple vs complex models/solutions in determining the right technique to employ for a business problem and develop and maintain a nuanced understanding of the data generated by the business, including fundamental limitations of the data. Youll leverage your proficiency in one or more approved programming languages (Java, Scala, Python, R), and ensure foundational programming principles in developing code (best practices, writes unit tests, code organization, basics of CI/CD etc.) are followed in developing the teams products/models. Youll not only stitch together basic data pipelines for a given problem and own design and implementation of individual components within Data Science/Tech applications, but also articulate the technical strategy, value of technology, and impact on the business. As you do so, youll collaborate with engineers, scientists, and business partners/product owners to create algorithmic solutions that are performant and integrated into applications. Well look to you to mentor and provide technical support within a team, including mentoring junior team members, and present your work and your teams work to business partners and other Data Sciences teams. With a deeper understanding of your functional area of responsibility, youll support agile ceremonies, collaborate with peers across multiple products, communicate and collaborate with business partners, and demonstrate an understanding of areas outside your scope of responsibility. The exciting part of retailIts always changing! Core responsibilities of this job are described within this job description.Job duties may change at any time due to business needs. About You: 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) and 6+ years of professional experience or equivalent industry experience Masters degree in Quantitative disciplines (Science, Operations Research, Technology, Engineering, Mathematics) Good knowledge and experience developing optimization, simulation, and statistical models Strong analytical thinking skills. Ability to creatively solve business problems, innovating new approaches where required Strong hands-on programming skills in Python, SQL, Hadoop/Hive. Additional knowledge of Spark, Scala, R, Java desired but not mandatory Good working knowledge of mathematical and statistical concepts, MILP, algorithms, and computational complexity Passion for solving interesting and relevant real-world problems using a data science approach Experience in implementing advanced statistical techniques like regression, clustering, PCA, forecasting (time series) etc. Able to produce reasonable documents/narrative suggesting actionable insights Excellent communication skills. Ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives Self-driven and results oriented; able to meet tight timelines Strong team player with ability to collaborate effectively across geographies/time zones Know More About us here: Life at Target- https://india.target.com/ Benefits- https://india.target.com/life-at-target/workplace/benefits Culture- https://india.target.com/life-at-target/belonging

: Kotak811 is a completely digital, in-your-phone, mobile bank. It was founded in 2016 to help India adapt, evolve, and eventually overcome the barrier of digital banking and make it accessible to all. Our sole aim is to bring you the excitement and ease of digital banking with the trust and reassurance of Kotak Mahindra Bank’s experience and legacy. Incubated by Kotak Mahindra Bank, Kotak811 is where innovation meets banking to offer the user the most seamless banking experience there has ever been. (Kotak 811 is a digital zero balance savings account that can be opened online by everyone (Indian residents only) which acts as a one-stop solution for all your financial needs and day to-day transactions.) Equal Employment OpportunityAll employment decisions shall be made without regard to age, race, creed, colour, religion, sex, national origin, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by the state, or local law. Kotak 811, is committed to providing equal employment opportunities RoleData Scientist 2 Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference

Role Value: This role plays a pivotal part in driving innovation through the development of advanced, ML-driven technologies. By aligning business goals with product strategy, the Product Owner helps shape high-impact solutions that bring measurable value to both internal stakeholders and end users. Key Responsibilities: Collaborate closely with Machine Learning and Engineering teams on advanced data extraction technologies (e.g., no-OCR, VLM-based extraction) Translate business needs into epics and user stories for development teams Align product goals with company strategy in coordination with Product Management Maintain a well-prioritized product backlog based on business value Work with stakeholders and data analysts to ensure data-driven product decisions Track product progress, performance, and deliverables across sprints Communicate effectively with globally distributed teams and stakeholders Stay updated with agile practices, ML/AI trends, and industry standards Required Experience & Qualifications: 3+ years as a Product Owner in an agile environment Familiarity with AI/ML patterns (e.g., VLM, LLMs) and experience working with ML-driven teams Technical aptitude with a fast-learning mindset Strong data orientation and analytical thinking Agile and/or SAFe framework knowledge Excellent attention to detail and communication skills Comfortable working in international, cross-functional environments Proficient in spoken and written English Nice to Have: Exposure to Regulatory Compliance Product Marketing experience Strong cross-cultural communication Advanced data analysis capabilities Knowledge of Biometric Security Standards Key Traits: Energetic, teachable, and eager to learn Follows SOPs with accuracy and discipline Collaborative and customer-focused Takes ownership with a proactive, problem-solving attitude Resilient and positive under pressure Role & responsibilities Preferred candidate profile

Project Role : Application Lead Project Role Description : Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills : SAP ABAP Development for HANA Good to have skills : NAMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Lead, you will lead the effort to design, build, and configure applications, acting as the primary point of contact. Your typical day will involve collaborating with various teams to ensure that application development aligns with business objectives, overseeing project timelines, and facilitating communication among stakeholders to drive successful outcomes. You will also engage in problem-solving activities, providing guidance and support to your team while ensuring adherence to best practices in application development. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Mentor junior team members to enhance their skills and knowledge.- Continuously assess and improve team processes to increase efficiency. Professional & Technical Skills: - Must To Have Skills: Proficiency in SAP ABAP Development for HANA.- Strong understanding of application design principles and methodologies.- Experience with SAP HANA database and its integration with ABAP.- Familiarity with Agile development practices and project management tools.- Ability to troubleshoot and resolve technical issues effectively. Additional Information:- The candidate should have minimum 7.5 years of experience in SAP ABAP Development for HANA.- This position is based at our Pune office.- A 15 years full time education is required. Project requirement:7-10 years of ABAP Development experienceS4 experience is a must with use of model development standards and technology (Fiori, CDS, Eclipse) including RIEFW (Report, Interface, Enhancement, Forms, Workflows).Must have worked in at least 2 separate modules of S/4 (MM, PP, SD, FI/CO)Preferability worked on at least 1 S4 end-to-end implementation.Should be playing a leadership role today.70% on incidents and 30% on projects.Dependable, Reliable, Coachable.Exhibited ability to follow established guidelines at all times.Ability to work and manage priorities independently.Work with other Trinseo analysts. Qualification 15 years full time education

Senior analyst with ML model experience for Regions Bank Job Description: Primary Responsibilities for a Risk Data Scientist on the BSA/AML/OFAC Model Development and Monitoring Team: Design and develop transaction monitoring scenarios. Improves segmentation for the scenarios/models using techniques such as clustering. Executes periodic tuning for the threshold parameters of the scenarios through sample collection. Develops post processing models to reduce the number of false positives generated by the scenarios using techniques such as rare event logistic regression and machine learning algorithms. Researches and develops algorithms that incorporates fuzzy logic for OFAC sanction screening and other types of screening processes. Develops post processing models that incorporate Natural Language Processing techniques to reduce the number of false positives. Implementation of models. Develops and executes ongoing monitoring plan to monitor the performance of the models. Documentation of the model development, especially the implementation process. Supports model validation activities. Ad hoc analysis to address requests from business partners. Requirements Bachelor s degree in Statistics, Data Science, Operations Research, Industrial Engineering, Mathematics, or Physics, AND six (6) years related experience. Master s degree in Statistics, Data Science, Operations Research, Industrial Engineering, Mathematics, or Physics, AND four (4) years related experience. OR PhD degree in Statistics, Operations Research, Industrial Engineering, Mathematics, or Physics, AND two (2) years related experience. Skills and Competencies High proficiency with Python, R, SAS, and SQL. Advanced data sourcing and management skills. Enhanced experience with web scraping. Knowledge and experience with CDSW platform. Experience with software development, especially deployment. Experience with classification models. Location: DGS India - Bengaluru - Manyata N1 Block Brand: Merkle Time Type: Full time Contract Type: Permanent

Senior analyst with ML model experience for Regions Bank Job Description: Primary Responsibilities for a Risk Data Scientist on the BSA/AML/OFAC Model Development and Monitoring Team: Design and develop transaction monitoring scenarios. Improves segmentation for the scenarios/models using techniques such as clustering. Executes periodic tuning for the threshold parameters of the scenarios through sample collection. Develops post processing models to reduce the number of false positives generated by the scenarios using techniques such as rare event logistic regression and machine learning algorithms. Researches and develops algorithms that incorporates fuzzy logic for OFAC sanction screening and other types of screening processes. Develops post processing models that incorporate Natural Language Processing techniques to reduce the number of false positives. Implementation of models. Develops and executes ongoing monitoring plan to monitor the performance of the models. Documentation of the model development, especially the implementation process. Supports model validation activities. Ad hoc analysis to address requests from business partners. Requirements Bachelor s degree in Statistics, Data Science, Operations Research, Industrial Engineering, Mathematics, or Physics, AND six (6) years related experience. Master s degree in Statistics, Data Science, Operations Research, Industrial Engineering, Mathematics, or Physics, AND four (4) years related experience. OR PhD degree in Statistics, Operations Research, Industrial Engineering, Mathematics, or Physics, AND two (2) years related experience. Skills and Competencies High proficiency with Python, R, SAS, and SQL. Advanced data sourcing and management skills. Enhanced experience with web scraping. Knowledge and experience with CDSW platform. Experience with software development, especially deployment. Experience with classification models. Location: DGS India - Bengaluru - Manyata N1 Block Brand: Merkle Time Type: Full time Contract Type: Permanent

Req ID: 26-088 Come Join Our Passionate Team! At Barracuda, we make the world a safer place. We believe every business deserves access to cloud-enabled, enterprise-grade security solutions that are easy to buy, deploy, and use. We protect email, networks, data and applications with innovative solutions that grow and adapt with our customers journey. More than 200,000 organizations worldwide trust Barracuda to protect them in ways they may not even know they are at risk so they can focus on taking their business to the next level. We know a diverse workforce adds to our collective value and strength as an organization. Barracuda Networks is proud to be an employer that complies with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity regardless of race, gender, religion, sex, sexual orientation, national origin, or disability. Envision yourself at Barracuda We at Barracuda are at the forefront of protecting our customers from email-borne threats and data leaks. As an Analyst you will be having an opportunity to work with a core team of Threat Analysts who are specialized in stopping malicious traffic and content from reaching our customers. What you ll be working on: Analyze attack patterns and data trends, identifying drift and anomalies. Conduct root cause analysis and develop hypotheses for missed attacks. Report findings to the ML team with impact assessments. Evaluate feature importance and model effectiveness. Build reports, queries, and dashboards for insights. Eligibility Criteria: Freshers from BTECH/BE in AI/ML only (No CSE/IT) Minimum with 70% aggregate in 10th, 12th & BTECH/BE Immediate Joiners from 2024/2025 pass-out batches. What you bring to the role: Knowledge in Python, Scala, SQL, Databricks, and Spark. Hands-on experience in ML model development (MLLib, TensorFlow, PyTorch, Scikit). Understanding of email security (spam/phishing) is a plus. Strong analytical, communication, and adaptability skills. Willingness to work in a fast-paced, shift-based environment. What you ll get from us: A team where you can voice your opinion, make an impact, and where you and your experience are valued. Internal mobility - there are opportunities for cross training and the ability to attain your next career step within Barracuda. In addition, you will receive equity, in the form of non-qualifying options. #LI-hybrid

. Ensure completion of experiments and generate accurate and reproducible data from experiments. Develop relevant models and validation of the same. Supervise and execute laboratory / pilot plant experiments pertaining to the relevant research area such as sample preparation using various methods, sample characterization using various analysis & evaluation of the concerned samples. Organize facilities for experiments in research such as chemicals, equipment, analytical methods etc. Participate in pilot plant operations / studies, utilize results as boundary conditions for model development Support to plant operations Collect data and conduct relevant analysis Uploading reports on portal Preparation of Internal Technical Report Education Requirement : PhD in Biology/Chemistry/Chemical Engineering with specialization in relevant research area Experience Requirement : Minimum 2-3 years of research experience Skills & Competencies : Conduct literature survey in the area of research and compile information for dissemination & critical analysis. Develop work method and prepare SOPs for experiments in research including designing & planning of experiments. Prepare/Use simulation models. Study technology offers/ process engineering documents Perform process engineering design activities such as using relevant tools Familiar with applicable guidelines /codes / standards / legislations relevant to field of research .

Quantitative development to implement and optimize algorithms for asset pricing, risk management, and trading strategies and migrate analytics from c++ to Python Writes secure and high-quality code using Python or C++ with limited guidance Required Candidate profile 3+ years of Python, C++ Quantitative finance background with strong experience in bonds Experience with calculating Risk or Pricing of asset classes

Skill required: Delivery - Credit Risk Modeling Designation: I&F Decision Sci Practitioner Sr Analyst Qualifications: Any Graduation Years of Experience: 5 to 8 years About Accenture Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. Visit us at www.accenture.com 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 About Accenture Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. Visit us at www.accenture.com 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

Join Our Team: Model Risk Management Financial Crime Analytics At Deloitte , our Model Risk Management (MRM) practice helps clients navigate the complex landscape of model risk across financial crime, regulatory compliance, and advanced analytics. Our team consists of top-tier professionals with backgrounds in Statistics, Mathematics, Physics, Finance, Financial Engineering, and PhDs in quantitative disciplines . We specialize in qualitative assessments and quantitative modeling across Market Risk, Credit Risk, Operational Risk, Liquidity Risk, and Fraud Risk aligned with key regulatory standards such as CCAR/Stress Testing, Basel II.5/III, CRD IV/CRR . We also work on the valuation of complex derivatives and structured products , leveraging our deep expertise in quantitative modeling and data analytics. What You’ll Do In this role, you'll contribute to cutting-edge financial crime risk initiatives and support leading global banks in strengthening their risk modeling frameworks. Key Responsibilities: Develop and maintain Financial Crime models , including AML Feeder Models and Sanction Screening Models, using statistical methods and robust documentation practices. Tackle complex data analytics problems in risk management and deliver actionable insights to enhance risk tools. Apply deep quantitative and conceptual expertise to design, validate, and enhance risk models aligned with banking regulatory standards. Use programming tools such as Python, R, SAS, and SQL for model development and deployment. Translate complex modeling concepts into simple language for diverse stakeholders — from executives to technical experts. Create technical documentation , model validation reports, and regulatory submissions. Required Skills & Experience Sound understanding of statistical and mathematical concepts : regression, classification, time series, hypothesis testing, distribution analysis, A/B testing, performance monitoring, etc. Hands-on experience with AI/ML techniques : ANN, Decision Trees, Ensemble Methods (e.g., XGBoost). Experience with vendor-based AML systems and models (e.g., Event Processor Next Gen, Quantifind, Customer Risk Assessment). Expertise in Financial Crime Case Generation Analytics . Proficient in R, Python, SAS, SQL , with experience deploying models into production and performing data calibration. Understanding of AML and sanction screening regulatory frameworks. Strong skills in technical writing , executive reporting, and stakeholder communication. Exceptional time management and multitasking ability in a dynamic, global work environment. Flexibility to work with US/UK counterparts during extended or overlapping shifts. Preferred Skills Solid data science foundation with an understanding of end-to-end data pipelines and model lifecycles. Experience working in a banking or consulting environment , ideally on financial crime or risk analytics projects. Qualifications Bachelor’s , Master’s , or Ph.D. in a relevant quantitative field (e.g., Statistics, Mathematics, Financial Engineering, Computer Science, or related disciplines).

JOb Responsibilities: The Data Scientists will leverage expertise in advanced statistical and modelling techniques to design, prototype, and build the next-generation analytics engines and services. They will work closely with the analytics teams and business teams to derive actionable insights, helping the organization in achieving its’ strategic goals. Their work will involve high levels of interaction with the integrated analytics team, including data engineers, translators, and more senior data scientists. Has expertise in implementing complex statistical analyses for data processing, exploration, model building and implementation Lead teams of 2-3 associate data scientists in the use case building and delivery process Can communicate complex technical concepts to both technical and non-technical audience Plays a key role in driving ideation around the modelling process and developing models. Can conceptualize and drive re-iteration and fine tuning of models Contribute to knowledge building and sharing by researching best practices, documenting solutions, and continuously iterating on new ways to solve problems. Mentors junior team members to do the same REQUIRED EDUCATION AND EXPERIENCE: Master’s degree in Computer Science, Statistics, Math, Operations Research, Economics, or a related field Advanced level programming skills in at least 1 coding language (R/Python/Scala) Practical experience of developing advanced statistical and machine learning models At least 2 years of relevant analytics experience Experience in using large database systems preferred Has developed niche expertise in at least one functional domain REQUIRED SKILLS: Ability to work well in agile environments in diverse teams with multiple stakeholders Experience of leading small teams Able to problem solve complex problems and break them down into simpler parts Ability to effectively communicate complex analytical and technical content High energy and passionate individual who can work closely with other team members Strong entrepreneurial drive to test new out of the box techniques Able to prioritize workstreams and adopt an agile approach Willing to adopt an iterative approach; experimental mindset to drive innovation LOCATION: Bangalore What’s in it for you ? Disruptive projects : Work on ‘ breakthrough’ digital-and-analytics projects to enable UPL’s vision of building a future ready organization. It involves deploy ing solutions to help us increase our sales, sustain our profitability, improve our speed to market, supercharge our R&D efforts, and support the way we work internally. Help us ensure we have access to the best business insights that our data analysis can offer us. Cross functional leadership exposure : Work directly under guidance of functional leadership at UPL, on the most critical business problems for the organization (and the industry) today. It will give you exposure to a large cross-functional team (e.g.: spanning manufacturing, procurement, commercial, quality, IT/OT experts), allowing multi-functional learning in D&A deployment Environment fostering professional and personal development : Strengthen professional learning in a highly impact-oriented and meritocratic environment that is focused on delivering disproportionate business value through innovative solutions. It will be supported by on-the-job coaching from experienced domain experts, and continuous feedback from a highly motivated and capable set of peers. Comprehensive training programs for continuous development through UPL's D&A academy will help in accelerating growth opportunities. Come join us in this transformational journey! Let’s collectively Change the game with Digital & Analytics!

JOb Responsibilities: The Data Scientists will leverage expertise in advanced statistical and modelling techniques to design, prototype, and build the next-generation analytics engines and services. They will work closely with the analytics teams and business teams to derive actionable insights, helping the organization in achieving its’ strategic goals. Their work will involve high levels of interaction with the integrated analytics team, including data engineers, translators, and more senior data scientists. Has expertise in implementing complex statistical analyses for data processing, exploration, model building and implementation Lead teams of 2-3 associate data scientists in the use case building and delivery process Can communicate complex technical concepts to both technical and non-technical audience Plays a key role in driving ideation around the modelling process and developing models. Can conceptualize and drive re-iteration and fine tuning of models Contribute to knowledge building and sharing by researching best practices, documenting solutions, and continuously iterating on new ways to solve problems. Mentors junior team members to do the same REQUIRED EDUCATION AND EXPERIENCE: Master’s degree in Computer Science, Statistics, Math, Operations Research, Economics, or a related field Advanced level programming skills in at least 1 coding language (R/Python/Scala) Practical experience of developing advanced statistical and machine learning models At least 2 years of relevant analytics experience Experience in using large database systems preferred Has developed niche expertise in at least one functional domain REQUIRED SKILLS: Ability to work well in agile environments in diverse teams with multiple stakeholders Experience of leading small teams Able to problem solve complex problems and break them down into simpler parts Ability to effectively communicate complex analytical and technical content High energy and passionate individual who can work closely with other team members Strong entrepreneurial drive to test new out of the box techniques Able to prioritize workstreams and adopt an agile approach Willing to adopt an iterative approach; experimental mindset to drive innovation

Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/ Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference.

Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development Deployment. Skill Sets key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation deployment. 3- Create great data stories with expertise in robust EDA and statistical inference

Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference

Role & responsibilities Support the management of core business activities across Models, relating to: (1) Model Design, Development, Validation & Implementation, (2) Model Portfolio, Risk Analytics & Risk Mitigation, (3) Model Monitoring, Control, Standards & Documentation, and (4) Model Governance The roleholder will be responsible for development of investment and wealth models - (i) designing and execution of product risk ratings for Mutual Funds, Bonds, Structured Products and Stocks. (ii) design and maintain the Strategic Asset Allocation (SAA) and Aladdin advisory model used for Advisory and Discretionary businesses. (iii) Help develop Artificial intelligence (AI) model applications for GPB&W business. (iv) Develop different propositions and client capabilities to support ESG investing framework, margin trading, etc. As an expert in investment product risk, they will also provide key enhancements into designing future state methodologies for investment models. Optimise Expected Credit Losses (ECL) and Risk Weighted Assets (RWAs) for the GPB&W Lombard and other asset backed securities. Work across GPB&W to effectively manage model risks, increase model coverage and implement globally consistent model systems, standards, policies, processes, methodologies and governance across all regions. Engage with stakeholders across all areas, business functions, and regions in identifying local regulatory issues, feeding these requirements into global model program design and ensuring compliance with global and local model regulations. Develop and review models according to feedback or requirements from our stakeholders, prepare pre-implementation validation reports for local use (countries or legal entities), develop models specific to a country or a business if required by regulators, support annual model validations, check the run, monitoring and validation of data, develop model prototypes, implement models, UAT of the models, and maintain official model documentation. Administrate global and local governance through the GPB&W Model Oversight Forum and other technical committees, IMR and Audit, oversight the global and local model output to ensure its being appropriately used, and support the local and global business teams in model use. Run the model, produce global and local results, rollout models to new legal entities as required, run stress tests, document the processes, calculation runs and checks, monitor the model, and statistically validate the input data (scenario and internal loss data). Enhance GPB&W Data infrastructure to support all credit models.

This role is will own the complete end-to-end program from conceptualization, to business model development, launch, sustenance and growth of enabling *newcustomer services through the Last Mile network. --Who we are looking for This role is for a candidate who is a builder who can take a new initiative from 0 to 1 : conceptualization, pilots, launch, and then taking it from 1 to 100 by stabilizing, creating systems, mechanisms for the program to continue functioning and growing. The successful candidate will be the winning combination of a strong stakeholder manager, with understanding of working with a geographically diverse and vast team from external store and delivery partners at one end of the spectrum to business stakeholders on the other, an analyst adept at modelling and building business cases and a sharp process expert who can build efficient scalable processes. In short, program-cum-process-manager-cum analyst, who would not love to be in the spotlight, rather BE the spotlight! 3+ years of team management experience 3+ years of program or project management experience 3+ years of working cross functionally with tech and non-tech teams experience 3+ years of delivering cross functional projects experience Experience defining program requirements and using data and metrics to determine improvements Experience implementing repeatable processes and driving automation or standardization Experience in data mining, data management, reporting, and SQL queries

Are you passionate about building scalable ML pipelines and deploying intelligent systems in the cloud? At Derisk360, we help transform businesses by combining AI expertise with deep domain knowledge. Were seeking a Senior ML Engineer to take our ML infrastructure to the next level using AWS SageMaker and state-of-the-art MLOps practices. What You ll Do: Develop, deploy, and manage ML models using AWS SageMaker, including pipelines, real-time endpoints, and batch transform jobs. Architect infrastructure using Infrastructure as Code (IAC) tools such as Terraform or AWS CloudFormation. Build robust, scalable solutions across real-time and batch systems with high reliability and performance. Design secure and scalable AWS networking environments tailored for ML workflows. Collaborate with data scientists, ML engineers, and DevOps to optimize model development and deployment pipelines. Contribute to automation, CI/CD pipelines, and monitoring strategies for ML systems. 7+ years of experience in software engineering, with at least 3+ years working on AWS SageMaker in production environments. Proficient in AWS services (EC2, S3, Lambda, IAM, VPC, CloudWatch) and deep understanding of AWS networking concepts. Solid experience with Terraform or CloudFormation for IAC implementation. Strong programming skills in Python and hands-on experience with ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Familiarity with model training, evaluation, versioning, and operationalizing in cloud environments. Experience integrating ML workflows with data lakes or data pipelines. Exposure to MLOps practices including experiment tracking, model registry, and containerization (Docker). Understanding of security best practices in AWS for machine learning. What You ll Get: Competitive salary with performance-based bonuses Lead innovative ML projects with top-tier insurance and risk-tech clients Work in a tech-forward, collaborative environment Opportunities to grow within a high-impact, AI-focused team Access to complex cloud-native platforms and enterprise-grade ML systems

Reference 23000TZY. Responsibilities. The missions of a senior functional expert are varied and hinge upon the strengthening of regulatory and accounting requirements related to the supervision and monitoring of risk models. In this context, you will be responsible for conducting internal model reviews (validation of the modeling, backtesting, etc.) that have been developed by the Group’s modeling entities.. Your main missions will be:. End to end responsibility of modeling validation missions, based on the planning and framework. Interact with the modeling entities. Analyze and test methods by using both technical knowledge and critical thinking.. Conduct quantitative reviews (statistics).. Be vigilant in the analysis of the regulatory compliance, robustness and performance of these models.. Contribute to the composition of a validation report in order to communicate the conclusions of the review mission.. Contribute and present the results of the review at the Models Committee. Ensure adequate documentation and archiving of the analyses carried out.. Mentoring Junior team members. The functional expert works on many different topics such as: retail or wholesale credit risk (PD models, CCF models, LGD models, stress tests), market risk models (VaR/SVaR/FRTB, EEPE, CVA, SIMM, IRC/CRM...), models developed under the IFRS 9 framework, models developed to comply with US regulatory requirements.. Required. Profile required. Ideal candidate should be well versed in credit risk model development, validation and maintenance of models (PD, LGD and EAD) for wholesale and retail credit portfolio of the bank as per regulatory guidelines.. Exposure to banking book and understanding of trading book products and knowledge on BASEL/IFRS guidelines is highly desirable. Candidate should have excellent business communication skills.. Educational Requirements:. Post-graduation degree in quantitative discipline(Statistics, Economics, Mathematics & engineering) from Tier I/II colleges. Additional certification in machine learning techniques or estimation of credit risk parameters will be preferred.. Role & Responsibility. The ongoing monitoring of the model is a task that must be done in all phases of the model lifecycle (development, implementation, use). In order to track and measure the efficiency and adequacy of models, the model monitor conducts continuous analysis and controls as an early warning both initially at implementation (for new models) and regularly as a part of the model’s ongoing monitoring.. For the purpose of these tests, the model monitor is responsible to:. Backtest & re-calibrate each model designed and developed by the business, hence a thorough understanding of model development under Basel & IFRS norms is critical.. Choose adequate model outcome analysis techniques such as:. Model estimates vs realized values (e.g. back-testing for some models);. Stability of model outcomes;. Benchmarking: model output vs output generated by comparable models or applications;. Sensitivity analysis to test robustness.. Analyze the model output and the related components (if applicable);. Model assumptions and limitations validity;. Results of benchmarking and sensitivity analysis;. Accuracy of model’s characteristics;(ROC/AUC, KS statistics, accuracy ratio, Gini coefficient etc). Monitor over time in order to follow up trends and detect deviations;. Establish thresholds and action plan for major deviations;. Report this analysis to the different model stakeholders.. Implement a governance to monitor the corrective actions. Furthermore, as part of the model ongoing monitoring phase, the model monitor should abide by the group standards on ongoing monitoring that establish guidelines on performance assessment processes including type, scope and range of tests and appropriateness of responses to any problems that may appear.. Technical Skills:. Regulatory risk model (IRB, IFRS9) model validation, monitoring, development (good to have) using SAS, R. Initiation to machine learning model validation.. Functional Skills:. –Knowledge of Global regulatory Topics BASEL II/III & IFRS 9. –Understanding of risk management and risk quantification processes. –Understanding of forms of risk, viz. credit, market, operational, model etc.. Behavioral Aspects:. Result Orientation. Client Focus. Contribution to Strategy. Cooperation. Team Player. Why join us. “We are committed to creating a diverse environment and are proud to be an equal opportunity employer. All qualified applicants receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status”.. Business insight. At Socit Gnrale, we are convinced that people are drivers of change, and that the world of tomorrow will be shaped by all their initiatives, from the smallest to the most ambitious. Whether you’re joining us for a period of months, years or your entire career, together we can have a positive impact on the future. Creating, daring, innovating, and taking action are part of our DNA. If you too want to be directly involved, grow in a stimulating and caring environment, feel useful on a daily basis and develop or strengthen your expertise, you will feel right at home with us!. Still hesitating?. You should know that our employees can dedicate several days per year to solidarity actions during their working hours, including sponsoring people struggling with their orientation or professional integration, participating in the financial education of young apprentices, and sharing their skills with charities. There are many ways to get involved.. We are committed to support accelerating our Group’s ESG strategy by implementing ESG principles in all our activities and policies. They are translated in our business activity (ESG assessment, reporting, project management or IT activities), our work environment and in our responsible practices for environment protection.. Diversity and Inclusion. We are an equal opportunities employer and we are proud to make diversity a strength for our company. Societe Generale is committed to recognizing and promoting all talents, regardless of their beliefs, age, disability, parental status, ethnic origin, nationality, gender identity, sexual orientation, membership of a political, religious, trade union or minority organisation, or any other characteristic that could be subject to discrimination.. Show more Show less

Date: Jun 5, 2025. Company: Zelestra. Location. Gurugram, India. About Us. Zelestra (formerly Solarpack) is a multinational company fully focused on multi-technology renewables with a vertically integrated business model focused large-scale renewable projects in rapidly growing markets across Europe, North America, Latin America, Asia, and Africa. Headquartered in Spain, Zelestra has more than 1000 employees worldwide and is backed by EQT, one of three largest funds in the world with $200B in assets.. One solution doesn’t fit all, especially in energy. We’re on a journey alongside our clients, assisting them in achieving their decarbonization goals. We are committed to developing tailored-made solutions by analyzing power market challenges and co-creating structured products based on customer insights.. One of the top 10 sellers of clean energy to corporates in the world, according to Bloomberg NEF, we are committed to tailored solutions to meet customer needs.. At Zelestra we aim to be a solid and solvent company, capable of executing quality and valuable projects for the society and the environment. Therefore, we maintain a firm commitment to contribute directly to the social development of the communities and markets in which we operate, not only through the creation of economic value, but also through the generation of quality employment and through the social projects we promote.. In the efforts of supporting business with innovative digital solutions, we want to recruit an experienced and dynamic Engineer.. Mission. We are looking for a motivated Junior Data Scientist to join our dynamic team, working on developing advanced Asset Performance Management solutions for solar plants and wind farms.. The ideal candidate will have hands-on experience in building time-series forecasting models, particularly in the context of renewable energy. You will work closely with our data scientists and engineers to deploy data-driven solutions, focusing on asset performance optimization, cloud tracking using image data, and leveraging large language models (LLM) for innovative solutions. If you’re passionate about data science and sustainability, we’d love to hear from you.. Responsibilities. Model Development & Analysis: Build, test, and deploy time-series models for solar and wind energy forecasting; develop asset performance models to predict equipment health and maintenance; collaborate with senior scientists to enhance model accuracy.. LLM and Image-Based Modelling: Use large language models for asset management solutions; create visualization models from satellite/drone imagery to optimize solar plant performance.. Data Visualization & Reporting: Develop clear visualizations and dashboards (using tools like Amazon QuickSight and PowerBI) to communicate insights and track renewable energy asset metrics.. Data Management & Collaboration: Handle large IoT datasets from renewable assets stored on cloud platforms (AWS S3, Azure Blob); maintain version control with Git/GitHub.. Model Deployment & Monitoring: Work with engineers to deploy models on cloud infrastructure (AWS, Azure); establish monitoring pipelines for ongoing model performance and updates.. Experience. Job Requirements. 0-2 years as a data scientist or related role, preferably with time-series modeling experience.. Practical skills in Python, R, or similar programming languages.. Technical Skills. Proficient in building and deploying time-series forecasting models.. Experienced with data visualization tools such as Power BI, Tableau, or equivalent.. Familiar with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.. Skilled in Git and version control for collaborative projects.. Cloud & Infrastructure. Experience with cloud platforms like AWS and Azure for data storage and processing.. Knowledge of cloud data lakes/data warehouses (AWS S3, Azure Blob Storage).. Collaboration & Communication. Ability to collaborate effectively with cross-functional teams, including engineers and data scientists.. Strong communication skills to translate technical findings into business strategies.. What We Offer. Career opportunities and professional development in a growing multinational company with a team highly qualified.. Flexible compensation.. Full working day.. Remote work 2 days a week.. Zelestra celebrates the diversity of thought and experience that comes from a variety of backgrounds including, among others, gender, age, ethnicity... Our mission is to contribute to a fairer and more equitable society.. JR2212. Show more Show less