1151 Statistical Modeling Jobs - Page 11

Educational Requirements MCA,Bachelor of Engineering,BCA Service Line Data & Analytics Unit Responsibilities Understand the requirements from the business and translate it into an appropriate technical requirements. Creating a detailed business analysis, outlining problems, opportunities and solutions for a business. Perform activities related to data wrangling, model building and model deployment. Stay current with the latest research and technology and communicate your knowledge throughout the enterprise. Lead initiatives to improve the team morale, camaraderie, and collaboration Technical and Professional Requirements: Generative AI, AI/ML, Python, Databricks Preferred Skills: Technology-Machine Learning-Generative AI

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

Returnship- Hiring Data science professionals Experience: 3 Years - 8 Years Location: Pan India JD: Data science- ML, Text analytics, Regression, Data classification and prediction, API’s Software’s:- python , power BI, sql, tableau. Platforms: H2O, Data robot Analytics code Deployment using Azure, AWS, on prem methods etc.

Clarivate offers proprietary market access data sets aggregated to provide a comprehensive view of todays healthcare ecosystem and offer invaluable insights from pre-launch through product maturity. We are looking for a Sr. Product Manager , reporting into the VP of Product Management for our Bangalore office. Across the Healthcare and Data Solutions organizationour focus remains on driving growthby product enhancements. About You education, experience, skills, and accomplishments Minimum bachelors degree in computer science, Statistics, Technology, or Engineering, or equivalent work experience, preferably with a data science background. Atleast 5 years in total working as a product manager, in the pharmaceutical analytics industry. A strong technical background coupled with an understanding of how data is leveraged to drive business outcomes in the pharmaceutical industry. Familiarity with analytics using SQL, SAS, Python, R, statistical modeling, and AI/ML techniques. Experience using JIRA and Confluence Ability to think and articulate clearly, concisely, and accurately for writing requirements. Excellent presentation and communication skills. Highly self-motivated, confident to work on projects alone as well as leading a team An enthusiastic approach to extending knowledge and learning new skills Strong commitment to quality of work and good attention to detail What you will be doing in this role Project management to shape the product strategy and delivering roadmap for Disease Intelligence & Analytics products. Utilize Real World Data (Claims, EHR, Pharmacy data etc.) for new products as well as enhancing existing products. Communicate the project requirements to key stakeholders. Bring teams together to define and implement product features and translate them into requirements. Ability to work well with internal teams, including developers, engineers, architects, quality assurance, and operations. Ensure requirements are fully understood and that implementation plans match expectations. Define success criteria for testing and product acceptance. Facilitate the creation and maintenance of proper product documentation. About the Team Its a small team working closely with various other teams like Content team, Technology team, UI/UX team etc. for the project Working Hrs Monday to friday - Candidate should be flexible as the time might cut across other timezone as well.

Job Summary We are seeking a Technical Lead with 10 to 14 years of experience in Analytics Analysis and Design with a strong background in Networks. The ideal candidate will work in a hybrid model during day shifts. This role does not require travel. The candidate will play a crucial role in driving technical excellence and innovation within the team. Responsibilities Lead the design and development of advanced analytics solutions to support business objectives. Oversee the analysis and interpretation of complex data sets to identify trends and insights. Provide technical guidance and mentorship to team members to ensure high-quality deliverables. Collaborate with cross-functional teams to define technical requirements and project scope. Develop and implement best practices for data analysis design and network management. Ensure the scalability reliability and performance of analytics solutions. Conduct regular code reviews to maintain code quality and adherence to standards. Troubleshoot and resolve technical issues related to analytics and network systems. Stay updated with the latest industry trends and technologies to drive innovation. Communicate effectively with stakeholders to understand their needs and provide technical solutions. Manage project timelines and deliverables to ensure timely completion of tasks. Contribute to the continuous improvement of processes and methodologies within the team. Document technical specifications and project progress for future reference. Qualifications Possess strong expertise in analytics analysis and design with a proven track record. Demonstrate in-depth knowledge of network systems and their management. Exhibit excellent problem-solving skills and attention to detail. Show proficiency in relevant programming languages and tools. Have experience in leading and mentoring technical teams. Display strong communication and collaboration skills. Be adaptable to a hybrid work model and day shifts. Maintain a proactive and innovative approach to technical challenges. Hold a relevant degree in Computer Science Engineering or a related field. Have a minimum of 10 years of experience in a similar role. Show commitment to continuous learning and professional development. Demonstrate the ability to work independently and as part of a team. Exhibit strong organizational and time management skills. Certifications Required Certified Analytics Professional (CAP) Cisco Certified Network Professional (CCNP)

We are looking for a Senior Data Scientist to join our Technology team at Clarivate. You will get the opportunity to work on interesting IP data and interesting challenges to create insights and drive business acumen to add value to our world class products and services About You experience, education, skills, and accomplishments Advanced degree in Computer Science, Statistics, Engineering, Physics, Mathematics, or other quantitative majors, or equivalent work experience. Atleast 4 years of industry experience in the application of ML and NLP Excellent understanding of ML, NLP, and statistical methodologies in a data analytics environment Good programming skills (Python, Java, R or C++) It would be great if you have, Experience with large language model Ability to test ideas and adapt methods quickly end to end from data extraction to implementation and validation Experience with search engines, classification algorithms, recommendation systems, and relevance evaluation methodologies What will you be doing in this role? Researches and identifies Machine Learning (ML) and Natural Language Processing (NLP) methods and algorithms to solve specific problems to improve user experience on IP & Science data and websites Implements these methods and devises appropriate test plans to validate and compare the different approaches Identifies new applications of ML and NLP in the context of Clarivate Analytics extensive sets of content and data Explores existing data for insights and recommends additional sources of data for improvements About the Team You would be part of our incredible data science team of Intellectual property (IP) group & work closely with product and technology teams spreads across various locations worldwide. Hours of Work This is a permanent position with Clarivate.9 hours per day including lunch break. you should be flexible with working hours to align with globally distributed teams and stakeholders.

We are looking for a Senior Data Scientist to join our Technology team at Clarivate. You will get the opportunity to work on interesting IP data and interesting challenges to create insights and drive business acumen to add value to our world class products and services About You experience, education, skills, and accomplishments Advanced degree in Computer Science, Statistics, Engineering, Physics, Mathematics, or other quantitative majors, or equivalent work experience. Atleast 4 years of industry experience in the application of ML and NLP Excellent understanding of ML, NLP, and statistical methodologies in a data analytics environment Good programming skills (Python, Java, R or C++) It would be great if you have, Experience with large language model Ability to test ideas and adapt methods quickly end to end from data extraction to implementation and validation Experience with search engines, classification algorithms, recommendation systems, and relevance evaluation methodologies What will you be doing in this role? Researches and identifies Machine Learning (ML) and Natural Language Processing (NLP) methods and algorithms to solve specific problems to improve user experience on IP & Science data and websites Implements these methods and devises appropriate test plans to validate and compare the different approaches Identifies new applications of ML and NLP in the context of Clarivate Analytics extensive sets of content and data Explores existing data for insights and recommends additional sources of data for improvements About the Team You would be part of our incredible data science team of Intellectual property (IP) group & work closely with product and technology teams spreads across various locations worldwide. Hours of Work This is a permanent position with Clarivate.9 hours per day including lunch break. you should be flexible with working hours to align with globally distributed teams and stakeholders.

We are looking for a Data Scientist to join our Technology team at Clarivate. You will get the opportunity to work on interesting IP data and interesting challenges to create insights and drive business acumen to add value to our world class products and services About You experience, education, skills, and accomplishments Advanced degree in Computer Science, Statistics, Engineering, Physics, Mathematics, or other quantitative majors, or equivalent work experience. Atleast 2 years of industry experience in the application of ML and NLP Excellent understanding of ML, NLP, and statistical methodologies in a data analytics environment Good programming skills (Python, Java, R or C++) It would be great if you have, Experience with large language model Ability to test ideas and adapt methods quickly end to end from data extraction to implementation and validation Experience with search engines, classification algorithms, recommendation systems, and relevance evaluation methodologies What will you be doing in this role? Researches and identifies Machine Learning (ML) and Natural Language Processing (NLP) methods and algorithms to solve specific problems to improve user experience on IP & Science data and websites Implements these methods and devises appropriate test plans to validate and compare the different approaches Identifies new applications of ML and NLP in the context of Clarivate Analytics extensive sets of content and data Explores existing data for insights and recommends additional sources of data for improvements

Salary : 25 to 40 LPA Exp: 4 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 : 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.

About Company Founded in 2011, ReNew, is one of the largest renewable energy companies globally, with a leadership position in India. Listed on Nasdaq under the ticker RNW, ReNew develops, builds, owns, and operates utility-scale wind energy projects, utility-scale solar energy projects, utility-scale firm power projects, and distributed solar energy projects. In addition to being a major independent power producer in India, ReNew is evolving to become an end-to-end decarbonization partner providing solutions in a just and inclusive manner in the areas of clean energy, green hydrogen, value-added energy offerings through digitalisation, storage, and carbon markets that increasingly are integral to addressing climate change. With a total capacity of more than 13.4 GW (including projects in pipeline), ReNew’s solar and wind energy projects are spread across 150+ sites, with a presence spanning 18 states in India, contributing to 1.9 % of India’s power capacity. Consequently, this has helped to avoid 0.5% of India’s total carbon emissions and 1.1% India’s total power sector emissions. In the over 10 years of its operation, ReNew has generated almost 1.3 lakh jobs, directly and indirectly. ReNew has achieved market leadership in the Indian renewable energy industry against the backdrop of the Government of India’s policies to promote growth of this sector. ReNew’s current group of stockholders contains several marquee investors including CPP Investments, Abu Dhabi Investment Authority, Goldman Sachs, GEF SACEF and JERA. Its mission is to play a pivotal role in meeting India’s growing energy needs in an efficient, sustainable, and socially responsible manner. ReNew stands committed to providing clean, safe, affordable, and sustainable energy for all and has been at the forefront of leading climate action in India. Job Description As a Senior Data Scientist, you will be responsible for providing simple and intuitive solutions to the most complex problems in renewable industry. This will involve building machine learning and deep learning models which are coupled with contextual business knowledge. You will also use both management experience and data science expertise to lead analytics projects and mentor junior data scientists . You will be an integral part of conceptualizing, scoping and delivering complex analytics projects . You will do and oversee the development, testing and maintenance of analytical models which mimic business decisions. You will work with a world-class team of site managers, subject experts, data engineers and data scientists to build the next generation data-driven renewable company. Additionally, you will be responsible for continuously identifying opportunities to improve the ways of working and structuring within the analytics center of excellence. Roles and Responsibilities Implement data science solutions which may involve machine learning or data science techniques to increase and optimize outputs Assess the effectiveness and accuracy of data sources and data gathering techniques Manage analytics strategy across multiple use cases Provide analytical expertise in the process of model development, refining and implementation in a variety of analytics problems spread across a variety of domains Oversee and mentor large team of associate and junior-level data scientists, de-bottlenecking issues related to project execution Work closely with translators and business teams to develop and implement analytics solutions Collaborate with the engineering team to integrate data science solutions into production environments and deploy scalable solutions Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner Acquire extensive knowledge of renewables industry practices and implement tailor made techniques to solve problems relevant to the same Promote a culture of continuous learning, sharing knowledge, and staying up-to-date with emerging technologies and best practices in data science Profile & Eligible Criteria Bachelor's in Computer Science, Data Science, Statistics, Mathematics, or a related field. Master's degree preferred Proven experience of 4-6 years as a Data Scientist or in a similar role, with a strong track record of delivering successful data science projects Sound theoretical and practical knowledge of working in statistical analysis, machine learning techniques, and deep learning frameworks with solid of understanding of techniques related to regression, classification, NLP, Computer Vision, Generative AI Proficiency in Python is a must. Proficiency in SQL for data manipulation is a plus Worked in developing analytics solutions in 3-4 domains Excellent communication skills to effectively manage a team and collaborate with stakeholders in cross-functional teams Communication skills: Basic level of articulation of theoretical concepts Ability to communicate with cross functional roles is a plus Teamwork: Displays ability to work both as an individual and as a self-motivated team player Has worked in large teams with an agile setup in the past

Job Description The GN SC&O - S&P - I&F Decision Sci Practitioner Sr Analyst is responsible for leveraging data analytics to inform and enhance supply chain decision-making processes. This role requires a strong analytical mindset and the ability to work collaboratively with various teams to drive improvements in inventory management and demand forecasting. Responsibilities Analyze data to support strategic decision-making in supply chain operations. Develop and implement advanced analytics models to optimize inventory and forecast demand. Collaborate with cross-functional teams to gather requirements and deliver actionable insights. Prepare and present analytical reports to stakeholders to drive business performance. Utilize data visualization tools to communicate findings effectively. Skills and Qualifications Bachelor's degree in Data Science, Statistics, Mathematics, or related field. 3-5 years of experience in data analysis, decision science, or supply chain analytics. Proficiency in statistical analysis tools such as R, Python, or SAS. Experience with data visualization tools like Tableau or Power BI. Strong understanding of supply chain processes and metrics. Excellent problem-solving and critical-thinking skills. Effective communication skills to convey complex data insights to non-technical stakeholders.

About Klook Klook is Asia's leading platform for experiences and travel services, dedicated to bringing the world closer together through unique and unforgettable experiences. Founded in 2014 by three passionate travelers - Ethan Lin, Eric Gnock Fah, and Bernie Xiong, Klook offers over half a million curated quality experiences in 2,700 destinations worldwide. From iconic attractions to adventurous activities like paragliding, from cultural tours to convenient local travel services, Klook aims to inspire and enable more moments of joy for travelers around the globe. Do you share our belief in the transformative power of travel Join our international community of over 1,800 employees across 30+ locations who are not only curating memorable experiences but also co-creating a world of joy within Klook. At Klook, we work hard and play hard, maintaining a high-performing culture guided by our six core values: Customer First, Push Boundaries, Critical Thinking, Build for Scale, Less is More, and Win as One. We constantly strive for excellence and believe in reaching greater heights in the ever-evolving travel industry. If you are passionate about travel and innovation, come be a part of our revolution! As a Data Scientist in the Pricing Strategy team, you will be instrumental in driving data-driven decision-making and optimizing pricing strategies. Your role will involve developing and implementing dynamic pricing models, predictive and prescriptive analysis, and contributing to revenue growth and market competitiveness. What You'll Do Dynamic Pricing Model Development: Create and implement advanced dynamic pricing models to optimize product pricing across different channels and markets. Predictive Analytics: Utilize predictive modeling techniques to forecast demand, market trends, and customer behavior for proactive pricing adjustments. Prescriptive Analysis: Use prescriptive analytics to identify optimal pricing strategies aligned with specific business objectives and constraints. Data Exploration and Analysis: Conduct thorough data exploration and analysis to extract valuable insights for informing pricing decisions. Model Evaluation and Refinement: Continuously assess and refine pricing models to ensure accuracy and effectiveness. Collaboration: Work closely with cross-functional teams such as marketing, sales, and finance to align pricing strategies with overall business goals. Stay Updated: Keep abreast of the latest advancements in data science and pricing optimization techniques. What You'll Need Master's degree or PhD in Data Science, Statistics, Computer Science, Economics, or a related field. 3-4 years of relevant experience in Data Science. Proficiency in Python or R for programming, data manipulation, analysis, and visualization using libraries like Pandas, NumPy, Matplotlib, and Seaborn. Knowledge of machine learning algorithms (e.g., regression, classification, clustering, time series analysis) and statistical modeling. Familiarity with data warehousing and cloud computing platforms (e.g., AWS, GCP, Azure) is a plus. Strong problem-solving and analytical skills. Ability to effectively communicate complex technical concepts to both technical and non-technical audiences. Passion for data-driven decision-making and a continuous learning mindset. Klook is committed to being an equal opportunity employer, welcoming talented and passionate individuals from diverse backgrounds. We believe in fostering an inclusive workplace where everyone has an equal opportunity to thrive. Join us in creating a supportive and inclusive culture where every individual belongs.,

The Company Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do and they push us to ensure we take care of ourselves, each other, and our communities. Job Description: Your way to impact Your day to day Build, enhance, and document CECL/IFRS9-compliant loss prediction models, leveraging PD/EAD/LGD frameworks and vintage loss rate methodologies. Conduct rigorous model performance testing, stress testing, and scenario analysis to ensure models are robust and regulatory-compliant. Collaborate cross-functionally with implementation, finance, accounting, risk, and external stakeholders to align on model outputs, definitions, and business needs. Clearly communicate analytic insights and model results to senior leadership, and provide expert support for regulatory exams and audit reviews. What do you need to bring Advanced degree in a quantitative discipline (e.g., statistics, mathematics, data science, computer science, engineering, or related field). Deep expertise in statistical modeling, machine learning, or econometrics applied to credit risk, knowledge and familiarity of CECL and IFRS9 regulatory requirements and modeling best practices is a plus. Strong technical skills working with large datasets using SQL, Python, R, or similar tools; experience with cloud-based platforms such as GCP is highly desirable. 5+ years of hands-on experience developing consumer or small business credit risk models, preferably within a CECL/IFRS9 framework. Excellent communication and collaboration skills, with strong business judgment and a passion for data-driven problem solving. Our Benefits: Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.,

As a Member Technical Staff I at Adobe, you will be an integral part of our engineering team in Bengaluru, collaborating with a talented group to work on impactful global projects. Your role involves developing and programming software algorithms to analyze and utilize data effectively in various environments. You will be responsible for communicating insights and algorithms clearly, employing machine learning and statistical modeling techniques to enhance system performance, and translating technical specifications into efficient code using current programming languages. Testing, debugging, and ensuring software quality are crucial aspects of your responsibilities, along with documenting installation and maintenance procedures for developed systems. Additionally, you will apply deep learning technologies to enable computers to understand and respond to complex scenarios and adapt machine learning to interactive products such as virtual reality, augmented reality, and robotics. Your qualifications should include proven experience in software algorithm development, a strong grasp of machine learning and deep learning technologies, proficiency in programming languages, and the ability to work with large-scale computing frameworks and data analysis systems. If you are a problem-solver with attention to detail, excellent communication skills, and the ability to collaborate effectively in a team-oriented environment, we invite you to join Adobe. Be part of a team dedicated to shaping the future of digital experiences and contributing to innovative projects that make a difference globally.,

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. In this role, you will play a key role in delivering key insights from corporate data sources to support planning and operations of the Sourcing, Procurement, and Third Party Risk teams, which sit within the Finance organization. You will develop reports and dashboard tools to visualize data for rapid and clear understanding and communication. Additionally, you will work with business partners to understand data requirements and implement processes for ensuring data integrity. Role Objectives - Create effective data visualizations/dashboards utilizing Power BI - Employ an understanding of statistical modeling and analysis frameworks to gain key insights from collected data and support the development of predictive data models - Perform initial clean-up and classification of datasets, apply transformations to ensure compliance with data dictionaries, source missing data, and trace the origin of any data quality issues. Your Profile - Maintain and run queries against corporate datasets to answer key business questions - Support exploratory analysis of existing data to uncover new trends and insights - Troubleshoot issues with reports and dashboards to enable continuous monitoring of important business performance metrics and support effective visualization of data - Work with Sourcing, Procurement, and Risk leadership and other business teams to develop key data questions and performance metrics - Establish your position as a resource to colleagues for advice on all aspects of data utilization, including capture, analysis, reporting, and prediction - Assist in delivering advice to business partners on data capture requirements for analysis and on the creation of metrics to capture performance insights Capgemini is a global business and technology transformation partner, helping organizations accelerate their dual transition to a digital and sustainable world while creating tangible impact for enterprises and society. With a responsible and diverse group of 340,000 team members in more than 50 countries, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. The company delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market-leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.,

You are an experienced Lead Model Developer/Validator with a strong background in credit risk modeling, particularly focusing on Internal Credit Risk Rating modeling. Your main responsibility will involve leading the development and validation of advanced credit risk models, including PD, EAD, LGD, with a special emphasis on Expert judgment-based PD models for Corporate, Specialized Lending, and Financial Institutions. Your role will require you to conduct thorough data preparation and preprocessing using tools such as SAS, Python, R, and SQL. You will collaborate with various stakeholders to analyze, interpret, and communicate complex model results and insights. Additionally, you will be responsible for creating technical documentation including regulatory compliance model documentation, test plans, validation reports, findings report, and business requirements documents where applicable. Continuous improvement of models will be a key aspect of your job, involving identifying optimization opportunities, implementing advanced modeling techniques, and enhancing model performance and predictive accuracy. Moreover, you will be expected to provide mentorship and technical guidance to junior team members, promoting a culture of knowledge sharing and professional development. To qualify for this position, you should have 5-10 years of hands-on experience in credit risk model development and validation, proven expertise in modeling across retail and wholesale credit portfolios, and advanced proficiency in SAS, Python, R, and SQL. A deep understanding of IFRS9 and CECL regulatory frameworks and guidance, exceptional analytical and problem-solving skills, as well as excellent written and verbal communication abilities are essential. Preferred qualifications include an advanced degree in Statistics, Mathematics, Economics, or a related field, professional certifications in risk management or financial modeling, experience with IRB modeling, machine learning/advanced statistical modeling techniques, and knowledge of Basel regulatory guidance. Your technical skills should encompass model development (PD, LGD, EAD, Qualitative PD Models), programming (SAS, Python, R, SQL), regulatory knowledge (IRB, IFRS9, CECL), statistical modeling, data preprocessing, and machine learning techniques. If you meet these qualifications and are looking for a challenging opportunity to leverage your expertise in credit risk modeling, this role offers a platform to lead and drive sophisticated credit risk modeling initiatives across various portfolios.,

Job Description: Key Responsibilities **Text Embeddings & NLP** -Must have 3+ Years of experience on traditional ML. -Must have 3+ Years of experience working as Data scientist. Design and implement pipelines leveraging text embeddings for semantic search, classification, clustering, and document retrieval. - Work with embedding techniques such as TF-IDF, Word2Vec, GloVe, FastText, and transformer-based models including BERT, Sentence-BERT, OpenAI, and Azure OpenAI embeddings. - Apply dimensionality reduction methods (PCA, t-SNE, UMAP) to analyze and visualize embedding spaces. - Use cosine similarity, Euclidean distance, and approximate nearest neighbor algorithms like FAISS and ScaNN for similarity search and clustering. - Integrate embedding outputs into downstream applications such as intent detection, topic modeling, semantic deduplication, document ranking, and retrieval systems. **Traditional Machine Learning & Statistical Modeling** - Build and deploy predictive models with logistic/linear regression, random forests, gradient boosting techniques (XGBoost, LightGBM), SVM, Naive Bayes, k-means, and hierarchical clustering. - Employ statistical inference techniques including hypothesis testing, confidence intervals, bootstrapping, Bayesian inference, multicollinearity diagnostics, residual analysis, and time series forecasting (ARIMA, SARIMA). - Evaluate model performance using ROC/Precision-Recall curves, AUC, confusion matrices, F1-score, lift/gain charts, and KS statistics. - Conduct feature selection via Lasso/Ridge regression, recursive feature elimination (RFE), and SHAP values for interpretability. **Experimentation & Causal Inference** - Design and analyze A/B and multivariate tests, DOE experiments, and sophisticated causal inference methods including propensity score matching, causal forests, and difference-in-differences. - Translate experimental results into clear, actionable business insights that drive measurable outcomes. **Data Engineering & Productionization** - Develop scalable data pipelines using PySpark, SQL, and Azure Data Factory on platforms including Azure Data Lake, Databricks, MongoDB, and Cosmos DB. - Deploy machine learning solutions with FastAPI, Docker containers, and Azure App Services endpoints, while monitoring model health with MLflow and model drift. **Collaboration & Leadership** - Partner effectively with engineering, product, and business teams to define problem statements and deliver impactful solutions. - Lead technical discussions, perform code reviews, and mentor junior data scientists to foster technical growth. - Communicate complex analytical insights clearly to both technical and non-technical stakeholders. Required Skills and Qualifications Hands-on experience in machine learning, statistical modeling, and NLP applications. - Deep expertise in text embeddings and their real-world applications. - Proficiency in Python, PySpark, and SQL. - Strong foundation in statistical inference, model diagnostics, and evaluation metrics. - Experience working with Azure cloud ecosystem, Databricks, and production deployment of ML models. - Proven ability to design, execute, and interpret experiments with statistical rigor. Preferred (Good-to-Have) Skills - Familiarity with transformer-based large language models (LLMs), LangChain, or OpenAI APIs. - Experience with MLOps tools such as MLflow and Github Actions CI/CD pipelines with Azure App Services. - Exposure to graph analytics, retrieval-augmented generation (RAG) pipelines, or agent-based systems. Day-to-Day Responsibilities You will architect and implement advanced NLP and machine learning pipelines leveraging diverse text embeddings for semantic search, classification, and clustering tasks. Applying sound statistical modeling and causal inference techniques, you will lead experimentation efforts and build scalable data workflows using PySpark, SQL, and Azure services. Cross-functional collaboration will be a core part of your role as you translate analytical insights into strategic business outcomes.

Assistant General Manager - Customer Delight: Job Summary: We arelooking for a dynamic and experienced Assistant General Manager (AGM) Customer Delight to lead and oversee large-scale contact centre operationsacross multiple processes. This role demands strong leadership, strategicvision, and operational expertise to drive superior customer service, enhancecustomer satisfaction, and optimize operational efficiencies across diverseteams and service channels. Key Responsibilities: Strategic Leadership & Operational Oversight: Provide leadership and direction for large contact centre operations involving multiple teams and processes, ensuring alignment with company goals and customer experience strategies. Should have managed more than 150+ FTEs spread across multiple processes/contact centres. Multi-Process Management: Oversee the delivery of multiple customer service processes (e.g., inbound/outbound calls, chat, email, social media support), ensuring consistent service quality and performance standards across channels. Team Management & Development: Manage, mentor, and motivate a large workforce including team leads, supervisors, and agents. Drive talent acquisition, training, succession planning, and career development programs. Performance Management & Analytics: Define and monitor comprehensive KPIs such as Customer Satisfaction (CSAT), Net Promoter Score (NPS), Average Handle Time (AHT), First Contact Resolution (FCR), and Service Level Agreements (SLAs). Utilize data analytics to identify trends, optimize workflows, and drive continuous improvements. Process Optimization & Innovation: Lead initiatives to streamline processes, improve operational efficiency, and enhance the customer journey through automation, technology upgrades, and best practices. Customer Escalations & Quality Assurance: Handle escalated customer issues promptly, ensuring effective resolution and maintaining customer trust. Oversee quality assurance programs to maintain high service standards. Budget & Resource Management: Develop and manage operational budgets, resource planning, and vendor relationships to support scalable and cost-effective contact centre operations. Compliance & Risk Management: Ensure all operations comply with regulatory requirements, data privacy laws, and company policies. Lead risk mitigation and business continuity planning. Cross-Functional Collaboration: Work closely with other departments such as IT, Sales, Marketing, and Product teams to align customer experience initiatives and resolve systemic issues impacting customer satisfaction. Automation and AI deployment Ensuring the right deployment of AI solutions which results in the overall contacts volume reduction and increased efficiency as well as the quality of service. Qualifications & Experience: Bachelors degree in Business Administration, Management, or related field; MBA or advanced degree preferred. Minimum 10 years of progressive experience in contact centre management or customer experience leadership roles. Proven experience managing large teams (100+ employees) across multiple processes in a complex contact centre environment. Strong strategic thinking, analytical skills, and data-driven decision-making abilities. Excellent leadership, communication, and interpersonal skills. Proficient in CRM platforms, workforce management, and contact centre technologies. Demonstrated ability to drive transformation and deliver results in fast-paced, high-pressure environments. Key Competencies: Strategic leadership & vision Multi-channel customer service expertise Large team & multi-process management Operational excellence & process improvement Data analytics & performance management Stakeholder management & collaboration Change management & innovation mindset

Position level: AI Specialist/Software engineering professional (Cant be a junior/fresher, needs to be middle to senior level person) Work Experience: Ideally, 4 to 5 years of working as a Data Scientist / Machine Learning and AI at a managerial position (end-to-end project responsibility). Slightly lower work experience can be considered based on the skill level of the candidate. About the job: Use AI-ML to work with data to predict process behaviors. Stay abreast of industry trends, emerging technologies, and best practices in data science, and provide recommendations for adopting innovative approaches within the product teams. In addition, championing a data-driven culture, promoting best practices, knowledge sharing, and collaborative problem-solving. Abilities: Knowledge about data analysis, Artificial Intelligence (AI), Machine Learning (ML), and preparation of test reports to show results of tests. Strong in communication with a collaborative attitude, not afraid to take responsibility and make decisions, open to new learning, and adapt. Experience with end-to-end process and used to make result presentation to customers. Technical Requirements: Experience working with real world messy data (time series, sensors, etc.) Familiarity with Machine learning and statistical modelling Ability to interpret model results in business context Knowledge of Data preprocessing (feature engineering, outlier handling, etc.) Soft Skill Requirements: Analytical thinking Ability to connect results to business or process understanding Communication skills Comfortable explaining complex topics to stakeholders Structured problem solving – Able to define and execute a structured way to reach results Autonomous working style – can drive a small project or parts of a project Tool Knowledge: Programming: Python (Common core libraries: pandas, numpy, scikit-learn, matplotlib, mlfow etc.); Knowledge of best practices (PEP8, code structure, testing, etc.) Code versioning (GIT) Data Handling: SQL; Understanding of data format (CSV, JSON, Parquet); Familiarity with time series data handling Infrastructure: Basic Cloud technology knowledge (Azure (preferred), AWS, GCP); Basic Knowledge of MLOps workflow Good to have: Knowledge of Azure ML, AWS SageMaker; Knowledge of MLOps best practices in any tool; Containerization and deployment (Docker, Kubernetes) Languages: English – Proficient/Fluent Location: Hybrid (WFO+WFH) + Availability to visit customer sites for meetings and work-related responsibilities as per the project requirement.

We are looking for a Data Scientist who will support building AI tools for customers The candidate should be skilled at using large data sets to find opportunities for product and process optimization The candidate must have a proven ability to drive business results with their databased insights The candidate must be comfortable working with a wide range of stakeholders and functional teams Primary Skills Python, AI, ML (Machine Learning) Gen AI Generative AI + RAG, NLP, LLM, Deep Learning, Computer Vision, AWS, Cloud Or Azure Open AI (Any Cloud) Experience- 5 to 16 Years Location - Pune If anyone is interested please share your updated resume on my email id - Devyani.Pillai2@ltimindtree.com

ECMS # 527228 Number of Openings 2 Duration of project 6 months will get extended No of years experience Total - 10+ Yrs exp Relevant experience 6+ yrs in Data Scientist Detailed job description - Skill Set: Data Scientist (10+ Years Experience) Job Title: Data Scientist / Senior Data Scientist Location: Bangalore / Hyderabad (should be able to come in to office 5 days / week) Job Summary: As a Data Scientist, you will design and implement machine learning models and advanced analytics solutions to solve complex business problems. You will work with large-scale data, build predictive models, and collaborate with engineering and product teams to deploy data-driven solutions. You will also lead initiatives in computer vision and deploy models using AWS services . Key Responsibilities: Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems. Design and implement computer vision solutions using CNNs, object detection, and image segmentation techniques. Deploy machine learning models using AWS services such as SageMaker, Lambda, S3, and API Gateway. Perform feature engineering, model selection, and hyperparameter tuning. Analyze experimental results and iterate on model improvements. Collaborate with data engineers to ensure data pipelines are robust and scalable. Communicate technical findings to non-technical stakeholders. Stay updated with the latest research and trends in data science and AI. Required Skills & Qualifications: Masters or PhD in Computer Science, Statistics, Mathematics, or a related field. Strong programming skills in Python (pandas, scikit-learn, TensorFlow, PyTorch). Solid understanding of machine learning algorithms and statistical modeling. Hands-on experience with computer vision libraries such as OpenCV, TensorFlow, or PyTorch. Experience deploying models on AWS using services like SageMaker, Lambda, and S3. Familiarity with big data tools (e. g. , Spark, Hadoop) and cloud platforms. Proficiency in SQL and data wrangling. Strong communication and collaboration skills. Mandatory Skills Data Scientist with Strong hands on skills in AI, ML models , computer Vision solutions, AWS Services , Python , Data Pipeline. Vendor Billing range (local currency /Day) 11500 INR per day Work Location Bangalore / Hyd Client office all 5 days resource need to work at client location Hybrid/Remote/WFO No BGV Pre/Post onboarding Pre Any particular shift timings No

Position Overview : We are seeking a skilled Statistical Programmer to join our clinical research team. The successful candidate will be responsible for programming, validating, and delivering statistical outputs for clinical trials while ensuring compliance with regulatory standards and industry best practices. Key Responsibilities : Programming & Data Management : - Develop and maintain SAS programs for clinical trial data processing, analysis, and reporting. - Map clinical trial data to CDISC standards (SDTM and ADaM) ensuring compliance with regulatory requirements. - Create and maintain analysis datasets following CDISC implementation guidelines. - Perform data validation and quality control checks to ensure data integrity. Documentation & Compliance : - Generate and maintain CDISC documentation including define.xml files, reviewer's guides, and annotated case report forms (aCRF). - Conduct Pinnacle21 validation checks and resolve any compliance issues. - Ensure all deliverables meet regulatory submission standards (FDA, EMA, etc.). - Maintain comprehensive programming documentation and version control. Statistical Analysis & Reporting : - Produce Tables, Listings, and Figures (TLFs) based on Statistical Analysis Plans (SAP). - Collaborate with biostatisticians to implement complex statistical analyses. - Support clinical study reports and regulatory submissions. - Perform ad-hoc analyses as requested by clinical teams. Cross-functional Collaboration : - Work closely with clinical data management, biostatistics, and regulatory affairs teams. - Participate in project meetings and provide technical expertise. - Support timeline planning and deliverable tracking. - Mentor junior programmers and provide technical guidance. Required Qualifications : Technical Skills : - Minimum 3+ years of experience as a statistical programmer in clinical research or pharmaceutical industry. - Advanced SAS programming skills with expertise in Base SAS, SAS/STAT, SAS/GRAPH, and SAS Macro language. - Strong understanding of clinical trials including study designs, endpoints, and regulatory requirements. - Proven experience with CDISC standards (SDTM and ADaM) and data mapping techniques. - Experience with CDISC documentation including define.xml, reviewer's guides, and aCRF preparation. - Hands-on experience with Pinnacle21 validation software and resolving compliance issues. - Demonstrated ability to produce TLFs based on Statistical Analysis Plans with attention to detail. Soft Skills : - Fluent in English with excellent written and verbal communication skills. - Strong problem-solving mentality with ability to troubleshoot complex technical issues. - Detail-oriented approach with commitment to accuracy and quality. - Excellent communication and interpersonal skills for effective team collaboration. - Fast learner with ability to adapt to new technologies and methodologies. - Strong organizational skills and ability to manage multiple priorities. Preferred Qualifications (Nice to Have) : - Real-World Data (RWD) experience including analysis of electronic health records, claims data, or registries. - Pharmacokinetic (PK) calculations experience and understanding of PK/PD modeling. - R programming skills for statistical analysis and data visualization. - Experience with other statistical software packages (Python, SPSS, etc.). - Knowledge of therapeutic areas and regulatory guidelines. - Experience with cloud-based platforms and version control systems. Education Requirements : - Bachelor's degree in Statistics, Mathematics, Computer Science, Life Sciences, or related field. - Advanced degree preferred but not required with relevant experience. This position offers an excellent opportunity for a skilled statistical programmer to contribute to meaningful clinical research while developing expertise in regulatory compliance and industry best practices.

Job Role: - Candidate should know end to end working and functioning of payment products viz. IMPS, UPI, RTGS, NEFT and cards and have demonstrated building analytics driven solutions to prevent frauds - Knowledge of Fraud management platforms is preferred - Responsible to Review Fraud trends across Digital and Cards payments and Implement Rules to detect and prevent frauds - Working knowledge of rule writing in FRMs like Falcon and Clari5 is required - Candidate has demonstrated experience in building credit risk models for Credit Cards using various Statistical models and Machine Learning models - Coding knowledge on Hadoop environment is added advantage - Should be able to work in minimum supervision Skills required: Building predictive Models/Machine Learning models and managing big data using Python and SAS is must. Education : M Tech/B Tech/Statistics degree is mandatory Location: Mumbai Presentation: Good written and verbal communication skills Prior experience in Analytics with BFSI for 2-3 years is a must Hands -on experience on following methods and techniques is required as role involves working with both structure and unstructured data Network Analysis(Graph theory) Link Analysis ( Market Basket/Sequence Analysis) Text mining & NLP Regressions ( eg. Logistic ) Classification methods (Decision Tree, Neural Networks, KNN, SVM) Anomaly detection methods

We are seeking an Analyst III Business Process Transactions to join our team in India. The ideal candidate will play a key role in analyzing and improving business processes and transactions to enhance efficiency and effectiveness. Responsibilities Analyze business processes and transactions to identify areas for improvement. Support the development and implementation of process improvement initiatives. Collaborate with cross-functional teams to gather requirements and provide insights. Generate reports and dashboards to track performance metrics and KPIs. Assist in preparing documentation related to business processes and transaction workflows. Skills and Qualifications Bachelor's degree in Business Administration, Finance, or a related field. Proficient in data analysis tools such as Excel, SQL, and data visualization software. Strong analytical and problem-solving skills. Excellent communication and interpersonal skills. Ability to work collaboratively in a team environment. Knowledge of business process modeling techniques and methodologies.