214 Linear Regression Jobs - Page 8

SUMMARY Open Position: FARMAR Responsibilities: Providing animals with food and water Ensuring the well-being of animals Engaging in agricultural activities and tending to palm trees Skills and Qualifications: Skilled in agricultural tasks Requirements Requirements: Capability to work on a farm At least 1 year of farming experience Benefits Specified Salary: 110 Accommodation and Meals: Accommodation is provided; meals are the worker’s responsibility. Working Hours: 10 hours per day Weekly Day Off: One day per week Required Languages: English Muslim or Christian.

Job Location: Bangalore or Pune We are seeking a highly skilled Data Scientist with expertise in Large Language Models (LLM), Cognitive AI, and Machine Learning to drive innovation in AI-driven solutions. The ideal candidate will have strong Python programming skills and a deep understanding of TensorFlow, PyTorch, NLP, and deep learning frameworks . You will work on cutting-edge AI/ML projects, leveraging generative AI and cognitive computing to build intelligent models that enhance business decision-making, with a strong focus on abuse detection, fraud prevention, and risk management Key Responsibilities: Develop and fine-tune Large Language Models (LLMs) to improve natural language understanding, text generation, and conversational AI. Design and implement cognitive AI models that enhance machine-human interactions and decision automation. Build fraud detection and abuse management models using advanced AI/ML techniques to identify anomalies, behavioral patterns, and security threats. Work with deep learning frameworks like TensorFlow, PyTorch, and Keras to build and optimize AI models. Utilize NLP techniques (tokenization, named entity recognition, sentiment analysis, text summarization) for unstructured data processing. Perform statistical analysis and hypothesis testing to drive data-driven insights. Use Numpy, Pandas, Scikit-learn for data preprocessing, feature engineering, and model evaluation. Deploy AI/ML models using MLOps, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure) . Work with big data technologies such as Spark,Dask, and Hadoop for large-scale data processing. Collaborate with cross-functional teams (engineering,product, and business teams) to integrate AI models into applications. Stay updated with the latest advancements in AI, cognitive computing, fraud detection, and generative models to enhance AI capabilities. Must-Have Skills: Programming: Python (Numpy, Pandas, Scikit-learn), SQL AI/ML Frameworks: TensorFlow, PyTorch, Keras Natural Language Processing (NLP): NLTK, SpaCy, Transformers, Hugging Face Cognitive AI & LLMs: OpenAI GPT, BERT, LLaMA, Bloom, LangChain Abuse & Fraud Detection: Anomaly detection, behavioral analytics, risk scoring models Big Data & Cloud: Spark, Hadoop, AWS/GCP/Azure MLOps & Deployment: Docker, Kubernetes, CI/CD pipelines Mathematical & Statistical Skills: Probability, Linear Algebra, Optimization Deep Learning & Neural Networks: CNN, RNN, Transformers, GANs Good-to-Have Skills: Experience with vector databases (FAISS, Pinecone, Weaviate) for AI search and retrieval. Hands-on experience with AutoML tools like H2O.ai, Google AutoML, or DataRobot. Familiarity with reinforcement learning and multi-agent systems . Exposure to AI ethics, model interpretability, and explainable AI (XAI) . Knowledge of Graph Neural Networks (GNNs) and Knowledge Graphs . Education & Experience: Bachelor's/Masters degree in Computer Science, Data Science, AI/ML, Mathematics, or a related field . 4-7 years of hands-on experience in AI/ML, cognitive computing, and NLP. Why Join Us? Work on cutting-edge AI projects with a team of experts. Opportunity to develop and deploy generative AI models for real-world applications. If you're passionate about cognitive AI, Abuse Management, LLMs, fraud detection, and data science , apply now!

Strong proficiency in Python and/or R for data analysis and modeling. Advanced SQL skills for data querying and transformation. Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Solid understanding of statistics, hypothesis testing, regression analysis, and data mining. Familiarity with cloud platforms (AWS, Azure, or GCP) and big data tools (Spark, Hadoop) is a plus. Excellent problem-solving skills and attention to detail.

Salary : 25 to 40 LPA Exp: 4 to 8 years Location :Noida/Gurugram/Bangalore Notice: Immediate to 30 days..!! Roles & responsibilities: 5+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Domain: Retail Banking / Credit Cards Location: Mumbai/ Bengaluru Experience: 3-5 years Industry: Banking / Financial Services (Mandatory) Why would you like to join us? TransOrg Analytics specializes in Data Science, Data Engineering and Generative AI, providing advanced analytics solutions to industry leaders and Fortune 500 companies across India, US, APAC and the Middle East. We leverage data science to streamline, optimize, and accelerate our clients' businesses. Visit at www.transorg.com to know more about us. What do we expect from you? Build and validate credit risk models , including application scorecards and behavior scorecards (B-score), aligned with business and regulatory requirements. Use advanced machine learning algorithms such as Logistic Regression, XGBoost , and Clustering to develop interpretable and high-performance models. Translate business problems into data-driven solutions using robust statistical and analytical methods. Collaborate with cross-functional teams including credit policy, risk strategy, and data engineering to ensure effective model implementation and monitoring. Maintain clear, audit-ready documentation for all models and comply with internal model governance standards. Track and monitor model performance, proactively suggesting recalibrations or enhancements as needed. What do you need to excel at? Writing efficient and scalable code in Python, SQL, and PySpark for data processing, feature engineering, and model training. Working with large-scale structured and unstructured data in a fast-paced, banking or fintech environment. Deploying and managing models using MLFlow, with a strong understanding of version control and model lifecycle management. Understanding retail banking products , especially credit card portfolios , customer behavior, and risk segmentation. Communicating complex technical outcomes clearly to non-technical stakeholders and senior management. Applying a structured problem-solving approach and delivering insights that drive business value. What are we looking for? Bachelors or masters degree in Statistics, Mathematics, Computer Science , or a related quantitative field. 35 years of experience in credit risk modelling , preferably in retail banking or credit cards. Hands-on expertise in Python, SQL, PySpark , and experience with MLFlow or equivalent MLOps tools. Deep understanding of machine learning techniques including Logistic Regression, XGBoost, and Clustering. Proven experience in developing Application Scorecards and behavior Scorecards using real-world banking data. Strong documentation and compliance orientation, with an ability to work within regulatory frameworks. Curiosity, accountability, and a passion for solving real-world problems using data. Cloud Knowledge, JIRA, GitHub(good to have)

Skill required: Insight Engine - Analytics Insights Designation: Analytics and Modeling Analyst Qualifications: Any Graduation Years of Experience: 3 to 5 years What would you do? We are seeking a Machine Learning Data Scientist with 2 to 3 years of hands-on experience to join our growing Insights and Analytics team. The ideal candidate will be proficient in building ML models using supervised and unsupervised learning techniques, comfortable working with Python-based ML libraries, and experienced in data preparation workflows. Familiarity with Microsoft's AI/ML ecosystem is a strong advantage. What are we looking for? Preferred (Strong Advantage): Hands-on experience with Azure Machine Learning Studio and Automated ML. Familiarity with Azure Cognitive Services for vision, language, and decision tasks. Experience working with Microsoft Fabric and Synapse ML integration. Qualifications: Bachelor s or Master's degree in Computer Science, Data Science, Engineering, or related field. 2–3 years of experience in applied machine learning and data science projects. Solid understanding of model training, validation, and deployment workflows. Experience working with version control (e.g., Git) and collaborative development environments.Nice to Have: Familiarity with tools that help automate and manage the process of building, testing, and deploying machine learning models (MLOps and CI/CD pipelines). Basic understanding of cloud-based architecture and APIs. Roles and Responsibilities: Develop and implement machine learning models using supervised and unsupervised techniques. Apply appropriate machine learning algorithms for prediction tasks (e.g., linear regression, decision trees, neural networks) and data segmentation (e.g., k-means clustering, hierarchical clustering) based on project needs. Perform data preprocessing, feature engineering, and model evaluation. Use Python libraries such as scikit-learn, TensorFlow, and others to build and test models. Analyse and manipulate structured datasets using notebooks (e.g., Jupyter). Collaborate with data engineers, analysts, and product teams to translate business problems into ML solutions. Document model performance, data flows, and process pipelines. Qualification Any Graduation

Position Summary This role will be responsible for in-patient journey analysis and working with patient-level data to develop a robust solution for the client's teams. An expert in Patient Analytics who can guide and lead the team supporting pharma clients Job Responsibilities Led the project from India working with onshore/ client stakeholders. Work closely with the project manager to define the algorithm, break down the problem into execution steps, and run the analysis Ensure high-quality analytics solutions/reports to the client Delivery role will include working with the team of junior analysts, solution brainstorming and design, execution, and communication of the analysis in the client-ready formats Contribute towards Axtria tools and capabilities as per the business requirements. Education Bachelor of Engineering in Statistics Work Experience Overall, 4-7 years of rich experience in marketing analytics with 3+ years of good hands-on experience in Market Mix Modeling / Promotion Response Modeling / Test & Control Proficiency in Statistical and Probabilistic methods such as multivariate regression, hierarchical modelling, Mixed Effect modelling, SVM, Decision-Trees, Random Forest, etc. Hands-on experience in Python, and good PowerPoint skills. Priority to the candidates with Marketing Mix modeling in the Pharmaceutical / Life Sciences Domain. Knowledge of Pharma data sets (sales/ promotions/ customer master) in the US/ ex-US is deeply appreciated. Attitude and willingness to learn, accept the challenging environment and have confidence in delivering the results within timelines. Behavioural Competencies Teamwork & Leadership Motivation to Learn and Grow Ownership Cultural Fit Project Management Communication Technical Competencies Python SQL EXCEL Machine Learning Pharma Commercial Know How Patient Data Analytics Know How Others

Oliver Wyman is looking for Manager - Data Science to join our dynamic team and embark on a rewarding career journey. Delegating responsibilities and supervising business operations Hiring, training, motivating and coaching employees as they provide attentive, efficient service to customers, assessing employee performance and providing helpful feedback and training opportunities. Resolving conflicts or complaints from customers and employees. Monitoring store activity and ensuring it is properly provisioned and staffed. Analyzing information and processes and developing more effective or efficient processes and strategies. Establishing and achieving business and profit objectives. Maintaining a clean, tidy business, ensuring that signage and displays are attractive. Generating reports and presenting information to upper-level managers or other parties. Ensuring staff members follow company policies and procedures. Other duties to ensure the overall health and success of the business.

Dear Candidate, We are hiring for senior Data Scientist at Goregaon Below are the details for the same Organocation- Leading NBFC Location - Goregaon Work Mode- Work From office Roles & Responsibilities: Understanding the challenges faced by the business and translate that into a data problem Handle data in various formats easily, including both structured and unstructured data Ability to work with multiple data sources Model/ strategy development and validation Model deployment Requirements: Should be from Banking & NBFC Worked on Bureau data Develop Model like- Logistic regression, XGBoost, Random Forest, etc (Different techniques of model development) Coding- Python, XQL, Pyspark, Etc (Python is mandatory) Risk, Collections, Marketing related scorecard will work Scorecard- Application SC, Behavior SC, Fraud SC Min Exp- 5 plus Must

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

Skills Required: Python, R, Statistics, Machine Learning, Deep Learning, Cluster Regression, Generative AI (GenAI) Responsibilities: Assist with the development, testing, and deployment of AI/ML models, including Generative AI (GenAI) solutions. Brainstorm and implement solutions by referencing research papers, scholarly articles, and industry best practices. Perform data mining using state-of-the-art methods to extract insights and enable predictive analytics. Process, cleanse, and verify the integrity of datasets , ensuring their usability for accurate analysis and model training. Conduct error analysis for demand, wind, and solar forecast models to identify and implement enhancements. Carry out manual computations for demand, wind, and solar forecasts, complementing automated systems when necessary. Perform in-depth analysis to uncover insights and solve complex problems within the renewable energy domain. Understand and optimise forecasting models using R and Python programming. Design and implement new scripts in R and Python to automate tasks and improve operational efficiency. Develop Generative AI applications , including scenario generation, predictive modelling, and domain-specific innovations. Collaborate with cross-functional teams to integrate GenAI solutions into forecasting workflows. Update project status for self-assigned tasks daily, ensuring clear communication and project alignment.

Practical in applying geometric concepts, with strong Python & SQL skills. Creative problem-solver, innovator, able to build agent-driven solutions. Senior dev with TDD, AWS knowledge preferred over Ph.D.

Lead Data Analyst About us: 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 hasn t 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 Target s global team and has more than 4,000 team members supporting the company s global strategy and operations. As a part of the Merchandising Analytics and Insights team, our analysts work closely with business owners as well as technology and data product teams staffed with product owners and engineers. They support all Merchandising strategic initiatives with data, reporting and analysis. Merchandising teams rely on this team of analysts to bring data to support decision making. PRINCIPAL DUTIES AND RESPONSIBILITIES As a Lead Data Analyst your responsibilities will be exploring data, technologies, and the application of mathematical techniques to derive business insights. Data analysts spend their time determining the best approach to gather, model, manipulate, analyze and present data. You will lead an agile team which requires active participation in ceremonies and team meetings. In this role, you ll have opportunities to continuously upskill to stay current with new technologies in the industry via formal training, peer training groups and self-directed education. This role specifically will support a new initiatives requiring new data and metric development. Your curiosity and ability to roll up guest level insights will be critical. The team will leveraging in store analytic data to measure the impact of promotions, product placement, or physical changes at any given store has on store operations, guest experience and purchase decisions. This new capability are still being defined, which allows for creative thinking and leadership opportunities. Job duties may change at any time due to business needs. Key Responsibilities *: Work with MC, Merch, Planning, Marketing, Digital, etc. teams to use data to identify opportunities, bridge gaps, and build advanced capabilities Partner with Product, DS, DE, etc. to determine the best approach to gather, model, manipulate, analyze and present data Develop data and metrics to support key business strategies, initiatives, and decisions Explore data, technologies, and the application of mathematical techniques to derive business insights Desired Skills & Experiences *: Ability to breakdown complex problems, identify root cause of the issue, and develop sustainable solutions Ability to influence cross-functional teams and partners at multiple levels of the organization Possess analytical skills (SQL, Python, R, etc.) to find, manipulate, and present data in meaningful ways to clients Desire to continuously upskill to stay current with new technologies in the industry via formal training, peer training groups and self-directed education About you (In terms of technical) B.E/B.Tech, M.Tech, M.Sc. , MCA - Overall 8-12 years of experience. And 6-8 years data ecosystem experience. Strong Architect of data capabilities and analytical tools. Proven experience to architect enterprise level Datawarehouse solutions and BI Implementations across Domo, Tableau & other Visualization tools. Provide expertise and ability to train and guide team to implement top design architectures to build next generation analytics Deep Big data experience. Should have solid experience in Hadoop ecosystem and its components around writing programs using Map-Reduce, experience in developing Hive and PySpark SQL and designing and developing Oozie workflows. Hands on experience in object oriented or functional programming such as Scala &/or Python/R or other open-source languages Strong foundational mathematics and statistics Experience in analytical techniques like Linear & Non-Linear Regression, Logistic Regression, Time-series models, Classification Techniques etc (In terms of soft skills for lead role) Strong stakeholder management with product teams and business leaders. Has strong problem solving, analytical skills and ability to manage ambiguity. Ability to communicate results of complex analytic findings to both technical /non-technical audiences and business leaders. Ability to lead change, work through conflict and setbacks . Experience working in an agile environment (stories, backlog refinement, sprints, etc.). Excellent attention to detail and timelines. Strong sense of ownership. Desire to continuously upskill to stay current with new technologies in the industry via formal training, peer training groups and self-directed education Useful Links- 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

We are looking for a Senior Applied Scientist to support the development of next-generation generative AI powered solutions for Oracle Analytics. You will be responsible for designing new approaches to natural language based interaction with structured data, creating agentic systems for multi-faceted data analysis, developing advanced personalization and customization techniques, and integrating your solutions into intelligent applications for industry verticals. You will conduct in-depth research, produce production-ready code, and collaborate with a cross-functional team to integrate your work into applications and services. This role requires deep expertise in machine learning, data science and generative AI, including LLMs (fine-tuning, adaptation, personalization), agents/agent frameworks, and tool orchestration. Preferred qualifications include practical experience with machine learning approaches for structured data, tabular representation learning, graph neural networks, time series modeling, and operations research/mathematical optimization. Candidates should have the demonstrated ability to design novel solutions that advance the state of the art in response to business requirements, as evidenced by publications in first-tier conferences or journals and impact on successfully deployed software products that operate at scale. Responsibilities Responsibilities: Collaborate with a larger science team to develop innovative science solutions in response to business requirements. Research and develop innovative approaches leveraging recent advances in generative AI, mathematical optimization, and machine learning for structured data. Write high quality code to power experiments and build models. Contribute to writing production model code. Collaborate with data engineers to provide guidelines for data collection and annotation. Collaborate closely with cross-functional teams to deliver solutions into various applications and products. Identify new opportunities for scientific exploration and evaluate emerging technologies. Qualifications and Experience: PhD in Computer Science, Mathematics, Statistics, Engineering, or a related field and a minimum of 5 years work experience in AI/Generative AI/Machine Learning in an industry setting. Publication record in first-tier journals or conferences. Hands-on experience in generative AI and model/application evaluation. Proficiency in Python, SQL, Spark. Strong understanding of machine learning algorithms and architectures Excellent problem-solving and analytical skills Strong communication abilities. Qualifications Career Level - IC3

Responsibilities: * Deliver engaging training sessions on data science principles using Python, R, Excel & SQL. * Design & develop AI/ML curriculum for corporate clients.

Bachelors/Master’s degree in Computer Science, Data Science, AI/ML, or related field. Strong programming experience in Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow). Solid experience in machine learning, NLP, and deep learning frameworks . Hands-on expertise in LLMs (OpenAI, Hugging Face Transformers, LangChain, RAG frameworks) . Knowledge of vector databases (Pinecone, Weaviate, FAISS, Milvus) for semantic search and retrieval-augmented generation. Experience with cloud AI services (AWS SageMaker, GCP Vertex AI, Azure ML). Strong skills in SQL and data visualization tools (Power BI, Tableau, or similar). Familiarity with MLOps and model lifecycle management . Excellent analytical, problem-solving, and stakeholder communication skills. Good to Have (Preferred): Experience with multi-modal LLMs (text + image, text + speech). Understanding of Reinforcement Learning from Human Feedback (RLHF) . Contributions to open-source NLP/LLM projects. Prior experience in financial services, healthcare, or e-commerce domain is a plus.

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

Salary : 30 to 45 LPA Exp: 6 to 10 years Location :Hyderabad (Hybrid) Notice: Immediate to 30 days..!! Roles & responsibilities: 5+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 5+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Entity :- Accenture Strategy & Consulting Job location :- Mumbai About S&C - Global Network :- Accenture Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition WHATS IN IT FOR YOU Accenture CFO & EV team under Data & AI team has comprehensive suite of capabilities in Risk, Fraud, Financial crime, and Finance. Within risk realm, our focus revolves around the model development, model validation, and auditing of models. Additionally, our work extends to ongoing performance evaluation, vigilant monitoring, meticulous governance, and thorough documentation of models. Get to work with top financial clients globally Access resources enabling you to utilize cutting-edge technologies, fostering innovation with the worlds most recognizable companies. Accenture will continually invest in your learning and growth and will support you in expanding your knowledge. Youll be part of a diverse and vibrant team collaborating with talented individuals from various backgrounds and disciplines continually pushing the boundaries of business capabilities, fostering an environment of innovation. What you would do in this role Engagement Execution Work independently/with minimal supervision in client engagements that may involve model development, validation, governance, strategy, transformation, implementation and end-to-end delivery of risk solutions for Accentures clients. Ability to manage workstream of large projects / small projects with responsibilities of managing quality of deliverables for junior team members. Demonstrated ability of managing day to day interactions with the Client stakeholders Practice Enablement Guide junior team members. Support development of the Practice by driving innovations, initiatives. Develop thought capital and disseminate information around current and emerging trends in Risk. Qualification Who we are looking for 7 - 12 years of relevant Risk Analytics experience at one or more Financial Services firms, or Professional Services / Risk Advisory with significant exposure to one or more of the following areas: Development, validation, and audit of: Credit Risk- PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting and Revenue Forecasting Models, IFRS9/CECL Loss Forecasting Models across Retail and Commercial portfolios Credit Acquisition/Behavior/Collections/Recovery Modeling and Strategies, 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 scenarios/alerts, Network Analysis Operational risk AMA modeling, operational risk reporting Conceptual understanding of Basel/CCAR/DFAST/CECL/IFRS9 and other risk regulations Experience in conceptualizing and creating risk reporting and dashboarding solutions. Experience in modeling with statistical techniques such as linear regression, logistic regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time series ARMA/ARIMA, ML interpretability and bias algorithms etc. Programing Languages - SAS, R, Python, Spark, Scala etc., Tools such as Tableau, QlikView, PowerBI, SAS VA etc. Strong understanding of Risk function and ability to apply them in client discussions and project implementation. Academic : Masters degree in a quantitative discipline mathematics, statistics, economics, financial engineering, operations research or related field or MBA from top-tier universities. Strong academic credentials and publications, if applicable. Industry certifications such as FRM, PRM, CFA preferred. Excellent communication and interpersonal skills. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

Project Role : Responsible AI Engineer Project Role Description : Assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Must have skills : Responsible AI Good to have skills : NAMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Responsible AI Engineer, you will assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical, and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Roles & Responsibilities:- Expected to be a SME with deep knowledge and experience.- Should have Influencing and Advisory skills.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Develop and implement responsible AI frameworks.- Conduct audits and assessments of AI systems for ethical compliance.- Collaborate with cross-functional teams to ensure responsible AI practices are integrated. Professional & Technical Skills: - Must To Have Skills: Proficiency in Responsible AI.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 15 years of experience in Responsible AI.- This position is based at our Pune office.- A 15 years full-time education is required. Qualification 15 years full time education

Project Role : Responsible AI Engineer Project Role Description : Assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Must have skills : Responsible AI Good to have skills : NAMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Responsible AI Engineer, you will assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical, and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Roles & Responsibilities:- Expected to be a SME with deep knowledge and experience.- Should have Influencing and Advisory skills.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Develop and implement responsible AI frameworks.- Conduct audits and assessments of AI systems for ethical compliance.- Collaborate with cross-functional teams to ensure responsible AI practices are integrated. Professional & Technical Skills: - Must To Have Skills: Proficiency in Responsible AI.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 15 years of experience in Responsible AI.- This position is based at our Pune office.- A 15 years full-time education is required. Qualification 15 years full time education

Project Role : Responsible AI Engineer Project Role Description : Assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Must have skills : Responsible AI Good to have skills : NAMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Responsible AI Engineer, you will assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical, and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Roles & Responsibilities:- Expected to be a SME with deep knowledge and experience.- Should have Influencing and Advisory skills.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Develop and implement responsible AI frameworks.- Conduct audits and assessments of AI systems for ethical compliance.- Collaborate with cross-functional teams to ensure responsible AI practices are integrated. Professional & Technical Skills: - Must To Have Skills: Proficiency in Responsible AI.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 15 years of experience in Responsible AI.- This position is based at our Pune office.- A 15 years full-time education is required. Qualification 15 years full time education

In the IBM Chief Information Office, you will be part of a dynamic team driving the future of AI and data science in large-scale enterprise transformations. We offer a collaborative environment where your technical expertise will be valued, and your professional development will be supported. Join us to work on challenging projects, leverage the latest technologies, and make a tangible impact on leading organisations. As a Data Scientist within IBM's Chief Information Office, you will support AI-driven projects across the enterprise. You will apply your technical skills in AI, machine learning, and data analytics to assist in implementing data-driven solutions that align with business goals. This role involves working with team members to translate data insights into actionable recommendations. Key Responsibilities Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimisation of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyse complex datasets and generate actionable insights. Learn and utilise cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. Collaboration: Ensure alignment to stakeholders’ strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree is strongly preferred Experience 5+ yearsof experience in data science, AI, or analytics with a focus on implementing data-driven solutions Experience with data cleaning, data analysis, A/B testing, and data visualization Experience with AI technologies through coursework or projects Technical Skills: Proficiency in SQL and Python for performing data analysis and developing machine learning models Knowledge of common machine learning algorithms and frameworkslinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience with cloud-based platforms and data processing frameworks Understanding of large language models (LLMs) Familiarity with IBM’s watsonx product suite Familiarity with object-oriented programming Analytical Skills: Strong problem-solving abilities and eagerness to learn Ability to work with datasets and derive insights Other Requirements: Good communication skills, with the ability to explain technical concepts clearly

About the role: As a Senior Data Scientist, you have a grounding in data analysis using tools in Python ecosystem and AWS. You also have a business sense for asking and answering fundamental questions to help shape key strategic decisions. This role involves thinking critically and strategically about video ad delivery as a technology, as a business, and as an operation to help broadcasters, distributors, and media companies transform and evolve their advertising practices through the use of data. Using proven design patterns, you will help identify opportunities for INVIDI and our clients to operate more efficiently and produce innovative and actionable quantitative models and analyses to address the challenges of marketing effectiveness and measurement. As a data scientist, you will do more than just crunch the numbers. You will work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust business practices according to your findings. Identifying the problem is only half the job; you also need to figure out the solution. You must be versatile, display leadership qualities and be enthusiastic to take on new problems as we continue to push technology forward. The position will report directly to the Technical Manager of Software Development and will be based in our Chennai, India office. Key responsibilities: Build business intelligence dashboards using AWS Quick sights, Tableau, Excel and power BI Design, develop and deploy Machine learning models using Linear regression, Classification, Neural networks, Time Series forecasting. Engage broadly within the organization to identify, prioritize, frame, and structure reporting problems Help define analytical direction and influence the direction of data engineering and infrastructure work Conduct end-of-the-end analyses, including data gathering, requirements specification, processing, analysis, ongoing deliverables, and presentations Translate analysis results into business recommendations Develop comprehensive understanding of video content inventory, scheduling, customer segmentation, video distribution, viewership data structures and metrics Recommend and implement strategies to solve business problems when availability of data is limited Work with very large data sets to glean useful insights that are valuable to the business. You must have: Bachelors degree in a computer science, information management systems, or Data Science discipline or equivalent practical experience 5-6 years of experience in statistical data analysis, linear models, multivariate analysis, stochastic models, and sampling methods 4-5 years of experience in data modelling in SQL databases 3-4 years of experience in Data visualization tools like AWS QuickSight, Tableau, Power BI 3-4 years of experience in EDA in Notebook based environments like Jupyter Notebook using Python Pandas, NumPy, Matplotlib, Seaborn 3+ years of experience with AWS services like S3, IAM, Redshift, Athena, and AWS SageMaker 2-3 years' experience designing data lakes, cloud data warehouses using Snowflake, Redshift and BigQuery 2-3 years' experience with one or more cloud service providers like AWS and GCP. Strong experience in A/B testing, experimental design, and statistical inference It would be very good if you have experience in: Experience in building marketing analytics dashboards Working with Scrum teams in an Agile way Experience with MLOps practices and model deployment pipelines Experience in the following domains: video content delivery, viewership measurement, advertising technology, digital advertising Physical Requirements: INVIDI is a conscious, clean, well-organized, and supportive office environment. Prolonged periods of sitting at a desk and working on a computer are normal. Note: Final candidates must successfully clear INVIDIs background screening requirements. Final candidates must be legally authorized to work in India. INVIDI has reopened its offices on a flexible hybrid model.

About The Role TBD Qualification TBD