3566 Data Scientist Jobs - Page 40

We have an exciting opportunity for you to leverage data science methods to deliver actionable insights across the Card business. As a Data Science Associate within the Card Data and Analytics team, you will leverage skills in building insights from advanced analytics, Gen AI / LLM tools, analysis, data querying, and extracting insights from big data to support our Credit Card business. This role is a hands-on mix of consulting know-how, analytical proficiency in statistics, data science, and machine learning/AI, proficiency in SQL/Python programming, visualization methods, and technologies. Job Responsibilities Leverage your knowledge and analytical skills to uncover novel use cases of Big Data analytics for the Credit Card business. Support development of data science / AIML use cases for the Card business. Help partners in the Card business define their business problems and scope analytical solutions. Build an in-depth understanding of the Card domain and available data assets. Research, design, implement, and evaluate analytical approaches and models. Perform ad-hoc exploratory analyses and data mining tasks on diverse datasets. Communicate findings and obstacles to stakeholders to drive delivery to market. Required Qualifications, Capabilities, and Skills Bachelor s degree in a relevant quantitative field required in an analytical field (e. g. , Statistics, Economics, Applied Math, Operations Research, other Data Science fields). 4+ years of hands-on experience with data analytics; experience evaluating complex business problems and devising recommendations. Exceptional analytical, quantitative, problem-solving, and communication skills. Excellent leadership, consultative partnering, and collaboration across teams. Knowledge of statistical software packages (e. g. , Python) and data querying languages (e. g. , SQL). Experience across a broad range of modern analytics tools (e. g. , Snowflake, Databricks, SQL, Spark, Python). Preferred Qualifications, Capabilities, and Skills Understanding of the key drivers within the credit card P&L is preferred. Financial services background preferred, but not required. Master s degree or equivalent in an analytical field. We have an exciting opportunity for you to leverage data science methods to deliver actionable insights across the Card business. As a Data Science Associate within the Card Data and Analytics team, you will leverage skills in building insights from advanced analytics, Gen AI / LLM tools, analysis, data querying, and extracting insights from big data to support our Credit Card business. This role is a hands-on mix of consulting know-how, analytical proficiency in statistics, data science, and machine learning/AI, proficiency in SQL/Python programming, visualization methods, and technologies. Job Responsibilities Leverage your knowledge and analytical skills to uncover novel use cases of Big Data analytics for the Credit Card business. Support development of data science / AIML use cases for the Card business. Help partners in the Card business define their business problems and scope analytical solutions. Build an in-depth understanding of the Card domain and available data assets. Research, design, implement, and evaluate analytical approaches and models. Perform ad-hoc exploratory analyses and data mining tasks on diverse datasets. Communicate findings and obstacles to stakeholders to drive delivery to market. Required Qualifications, Capabilities, and Skills Bachelor s degree in a relevant quantitative field required in an analytical field (e. g. , Statistics, Economics, Applied Math, Operations Research, other Data Science fields). 4+ years of hands-on experience with data analytics; experience evaluating complex business problems and devising recommendations. Exceptional analytical, quantitative, problem-solving, and communication skills. Excellent leadership, consultative partnering, and collaboration across teams. Knowledge of statistical software packages (e. g. , Python) and data querying languages (e. g. , SQL). Experience across a broad range of modern analytics tools (e. g. , Snowflake, Databricks, SQL, Spark, Python). Preferred Qualifications, Capabilities, and Skills Understanding of the key drivers within the credit card P&L is preferred. Financial services background preferred, but not required. Master s degree or equivalent in an analytical field.

Candidate Candidate LTIMindtree Hiring for Data Scientist (GEN AI) Location: Pan India Experience: 8 to 16 years Mandatory Skills - Data Scientist, Machine Learning, Deep learning, GEN AINotice Period - Immediate to 45 days of NP Job Description : Job descriptionWe are looking for a highly skilled and results-driven Experienced Data Scientist to be at the forefront of developing and implementing Generative AI solutions that address critical business challenges and unlock new opportunities. This individual will leverage their deep expertise in data science, machine learning, and specifically Generative AI techniques to drive impactful projects from ideation to deployment. They will develop AI & ML solutions to tackle complex business challenges and facilitate data-driven decision-making through hands-on work with large datasets and strong collaboration with cross-functional teams to deliver significant results. Responsibilities: Data Handling & Preparation: Work with diverse and large-scale datasets. Perform data cleaning, preprocessing, feature engineering, and create synthetic datasets as needed for training and evaluating Generative AI models. Ensure data quality and integrity throughout the model development lifecycle. Model Optimization & Deployment: Optimize Generative AI models for performance, scalability, efficiency, and responsible AI considerations (bias detection and mitigation, hallucination reduction). Collaborate with Machine Learning Engineers and DevOps teams to deploy models into production environments and establish monitoring frameworks. Prompt Engineering & Fine-tuning: Develop effective prompts and fine-tuning strategies for Large Language Models to achieve desired outputs and adapt models to specific domains and tasks. Generative AI Model Development & Implementation: Design, develop, train, fine-tune, and deploy various Generative AI models, including but not limited to Large Language Models (LLMs), diffusion models, Generative Adversarial Networks (GANs), and Variational Autoencoders (VAEs), for applications If Interested , Kindly share me your updated CV with below details - Pramoth@ltimindtree.com Candidate Name - Candidate Email ID - Candidate Mobile Number - Total Years of IT experience - Relevant Years of Data Scientist Experience - Current CTC - Expected CTC - Any Offers in hand or Pipeline - Notice Period (If serving then LWD)-

Inviting applications for the role of Lead Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities • Collaborate with cross-functional teams to identify, analyze, and interpret complex datasets to develop actionable insights and drive data-driven decision-making. • Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Experience in data science, machine learning, AI applications, and generative AI modelling. Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills • Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills.

Remote Work: Hybrid Overview: At Zebra, we are a community of innovators who come together to create new ways of working to make everyday life better. United by curiosity and care, we develop dynamic solutions that anticipate our customer s and partner s needs and solve their challenges. Being a part of Zebra Nation means being seen, heard, valued, and respected. Drawing from our diverse perspectives, we collaborate to deliver on our purpose. Here you are a part of a team pushing boundaries to redefine the work of tomorrow for organizations, their employees, and those they serve. You have opportunities to learn and lead at a forward-thinking company, defining your path to a fulfilling career while channeling your skills toward causes that you care about locally and globally. We ve only begun reimaging the future for our people, our customers, and the world. Let s create tomorrow together. We are seeking a highly skilled and motivated Data Scientist (LLM Specialist) to join our AI/ML team. This role is ideal for an individual passionate about Large Language Models (LLMs) , workflow automation, and customer-centric AI solutions. You will be responsible for building robust ML pipelines , designing scalable workflows, interfacing with customers, and independently driving research and innovation in the evolving agentic AI space . Key Responsibilities: LLM Development & Optimization: Train, fine-tune, evaluate, and deploy Large Language Models (LLMs) for various customer-facing applications. Pipeline & Workflow Development: Build scalable machine learning workflows and pipelines that facilitate efficient data ingestion, model training, and deployment. Model Evaluation & Performance Tuning: Implement best-in-class evaluation metrics to assess model performance, optimize for efficiency, and mitigate biases in LLM applications. Customer Engagement: Collaborate closely with customers to understand their needs, design AI-driven solutions , and iterate on models to enhance user experiences. Research & Innovation: Stay updated on the latest developments in LLMs, agentic AI , reinforcement learning with human feedback (RLHF), and generative AI applications. Recommend novel approaches to improve AI-based solutions. Infrastructure & Deployment: Work with MLOps tools to streamline deployment and serve models efficiently using cloud-based or on-premise architectures, including Google Vertex AI for model training, deployment, and inference. Foundational Model Training: Experience working with open-weight foundational models , leveraging pre-trained architectures, fine-tuning on domain-specific datasets, and optimizing models for performance and cost-efficiency. Cross-Functional Collaboration: Partner with engineering, product, and design teams to integrate LLM-based solutions into customer products seamlessly. Ethical AI Practices: Ensure responsible AI development by addressing concerns related to bias, safety, security, and interpretability in LLMs. Responsibilities: Experience: experience in ML, NLP, or AI-related roles, with a focus on LLMs and generative AI . Programming Skills: Proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch LLM Expertise: Hands-on experience in training, fine-tuning, and deploying LLMs (e.g., OpenAI s GPT, Meta s LLaMA, Mistral, or other transformer-based architectures). Foundational Model Knowledge: Strong understanding of open-weight LLM architectures , including training methodologies, fine-tuning techniques, hyperparameter optimization, and model distillation . Data Pipeline Development: Strong understanding of data engineering concepts , feature engineering, and workflow automation using Airflow or Kubeflow . Cloud & MLOps: Experience deploying ML models in cloud environments like AWS, GCP (Google Vertex AI), or Azure using Docker and Kubernetes . Model Serving & Optimization: Proficiency in model quantization, pruning, distillation, and knowledge distillation to improve deployment efficiency and scalability. Research & Problem-Solving: Ability to conduct independent research , explore novel solutions , and implement state-of-the-art ML techniques. Strong Communication Skills: Ability to translate technical concepts into actionable insights for non-technical stakeholders. Version Control & Collaboration: Proficiency in Git, CI/CD pipelines , and working in cross-functional teams . Qualifications: Bachelor s in Computer Science, Machine learning, or related discipline.Master s preferred Strong background in statistics, machine learning, deep learning and programming necessary. 5+years experience required Experience in solving large-scale real-world industry problems, preferably in collaboration with cross-functional, multi-disciplinary teams Knowledge of statistical programming techniques and languages (e.g., R, Python, Java, etc.) Working knowledge of common machine learning and deep learning approaches (e.g. regression, clustering, classification, dimensionality reduction, supervised and unsupervised techniques, Bayesian reasoning, boosting, random forests, deep learning) and data analysis packages (e.g. scikit-learn, pyclustering, pathways analysis, MLlib) Prior experience with Tensorflow Prior experience in Natural Language Processing using NLTK Retail industry experience desired Experience using cloud compute (e.g. Google Cloud Platform, AWS, Azure) Familiarity with NoSQL databases, graphical analyses, and large-scale data processing frameworks (e.g. Apache Spark) Solid understanding of data structures, software design and architecture Ability to work independently and take initiative, but also a co-operative team player To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you via @zebra.com email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department. ", "

Data Scientist for Market Research Job Description : Role Overview: We are seeking a highly skilled Data Scientist with strong analytical programming capabilities and experience working with large-scale datasets The role involves driving analytics-led market estimations, model development using LLMs, and supporting new product initiatives Key Responsibilities: Clean, process, and analyze large datasets for actionable insights and market extrapolations Develop and deploy AI/ML models, including use of LLMs for market intelligence automation and new product development Support the development of analytics modules and tools aligned to business and client needs Apply statistical and predictive modeling to generate actionable insights for client decision-making Candidate Profile : Required Qualifications: Bachelor s degree in Statistics, Computer Science, Data Science, or related fields 2-3 years of relevant experience a must Strong programming skills in Python and SQL Experience with AI/ML frameworks such as TensorFlow, PyTorch, and LLM-based workflows Familiarity with cloud platforms (AWS, GCP) and model deployment practices Tier 1/Tier 2 academic background preferred

The Data Scientist role at Scienaptic will enable you to be at the forefront of latest cutting- edge technology and create a significant and visible business impact for Scienaptic. You will be working with some of the best-in-class Engineers, Data Scientists, and Business Analytics Consultants in an environment which will encourage you to contribute widely to functional and technological aspects without worrying about conventional job silos. Responsibilities Design, develop, and deploy machine learning based models for credit risk and related use cases. Present model outcomes and recommendations to internal and external stakeholders. Establish a regular cadence of client engagement including roadmap planning, updates, and reporting. Establish model monitoring, back-testing, and performance tracking frameworks. Work closely with internal teams including Client Engagement, Engineering and Product to ensure smooth integration and deployment. Skills & Competencies 4+ years of experience in data science and machine learning with prior experience in credit risk model development. Strong proficiency in Python for data analysis and model development. Sound knowledge of supervised and unsupervised machine learning techniques. Strong communication and presentation skills - ability to explain complex models to stakeholders. Experience managing client relationships or working in a consulting environment Bachelor/master s degree in a quantitative discipline (e.g., Statistics, Economics,

We are looking for a highly skilled and experienced Data Scientist to join our Common Data Model (CDM) team within the Data Science and Credit Risk function. This role is pivotal in ensuring the integrity, scalability, and performance of our credit risk models by developing, maintaining, and quality-controlling the input mapping and data rollup logic that powers our decisioning infrastructure. As a senior member of the team, you will lead a small team of data scientists and collaborate closely with engineering, product, and integration teams to translate various data sources into standardized features used in risk models and strategies. Responsibilities Own the design, development, and maintenance input mapper and rollup logic for credit bureau, core banking, internal datasets and any additional data sources in the future. Ensure accuracy, performance, and compliance through rigorous QC frameworks and automated validation tools. Collaborate with credit risk, product, engineering, and integration teams to deploy and support model and strategy features in production environments. Analyse complex datasets and derive accurate business logic in alignment with credit policy and model requirements. Lead and mentor a team of data scientists and analysts, ensuring adherence to best practices in software engineering and data science. Contribute to data governance, documentation, and version control of the CDM and associated tooling. Skills & Competencies 5+ years of experience in Data Science/Data Engineering/Analytics Strong Python skills ability to writing clean, testable, modular, and production-grade code. Experience in credit risk, fintech, or financial services domains. Experience working on US credit bureau data Prior experience managing or mentoring technical teams. Strong communication skills and the ability to work cross-functionally with engineers, product managers, and stakeholders. Bachelor s / master s degree in a quantitative discipline (e.g. Engineering, Computer Science, Mathematics). Scienaptic is on a mission to increase credit availability by transforming technology used in credit decisioning. Over 150 years of credit experience is embedded in Scienaptic s AI native credit decision platform. Our clients across banks, credit unions, fintech, and other lenders use the platform to constantly improve the quality of underwriting decisions. This enables them to say yes to borrowers more often and faster.

Responsibilities Position responsibilities and expectations Designing and building analytical /DL/ ML algorithms using Python, R and other statistical tools. Strong data representation and lucid presentation (of analysis/modelling output) using Python, R Markdown, Power Point, Excel etc. Ability to learn new scripting language or analytics platform. Technical Skills required (must have) HandsOn Exposure to Generative AI (Design, development of GenAI application in production) Strong understanding of RAG, Vector Database, Lang Chain and multimodal AI applications. Strong understanding of deploying and optimizing AI application in production. Strong knowledge of statistical and data mining techniques like Linear & Logistic Regression analysis, Decision trees, Bagging, Boosting, Time Series and Nonparametric analysis. Strong knowledge of DL & Neural Network Architectures (CNN, RNN, LSTM, Transformers etc.) Strong knowledge of SQL and R/Python and experience with distribute data/computing tools/IDEs. Experience in advanced Text Analytics (NLP, NLU, NLG). Strong handson experience of endtoend statistical model development and implementation Understanding of LLMOps, ML Ops for scalable ML development. Basic understanding of DevOps and deployment of models into production (PyTorch, TensorFlow etc.). Expert level proficiency algorithm building languages like SQL, R and Python and data visualization tools like Shiny, Qlik, Power BI etc. Exposure to Cloud Platform (Azure or AWS or GCP) technologies and services like Azure AI/ Sage maker/Vertex AI, Auto ML, Azure Index, Azure Functions, OCR, OpenAI, storage, scaling etc. Technical Skills required (Any one or more) Experience in video/ image analytics (Computer Vision) Experience in IoT/ machine logs data analysis Exposure to data analytics platforms like Domino Data Lab, c3.ai, H2O, Alteryx or KNIME Expertise in Cloud analytics platforms (Azure, AWS or Google) Experience in Process Mining with expertise in Celonis or other tools Proven capability in using Generative AI services like OpenAI, Google (Gemini) Understanding of Agentic AI Framework (Lang Graph, Auto gen etc.) Understanding of finetuning for pretrained models like GPT, LLaMA, Claude etc. using LoRA, QLoRA and PEFT technique. Proven capability in building customized models from opensource distributions like Llama, Stable Diffusion Mandatory skill sets AI chatbots, Data structures, GenAI objectoriented programming, IDE, API, LLM Prompts, Streamlit Preferred skill sets AI chatbots, Data structures, GenAI objectoriented programming, IDE, API, LLM Prompts, Streamlit Years of experience required 36 Years Education qualification BE, B. Tech, M. Tech, M. Stat, Ph.D., M.Sc. (Stats / Maths) Education Degrees/Field of Study required Doctor of Philosophy, Bachelor of Engineering, Bachelor of Technology Degrees/Field of Study preferred Required Skills Chatbots, Data Structures, Generative AI Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, C++ Programming Language, Communication, Complex Data Analysis, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Machine Learning, Machine Learning Libraries, Named Entity Recognition, Natural Language Processing (NLP), Natural Language Toolkit (NLTK) {+ 20 more} Travel Requirements Government Clearance Required?

Not Applicable Specialism Data, Analytics & AI Management Level Associate & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decisionmaking and driving business growth. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decisionmaking and automation. At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purposeled and valuesdriven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us . Responsibilities Position responsibilities and expectations Designing and building analytical /DL/ ML algorithms using Python, R and other statistical tools. Strong data representation and lucid presentation (of analysis/modelling output) using Python, R Markdown, Power Point, Excel etc. Ability to learn new scripting language or analytics platform. Technical Skills required (must have) HandsOn Exposure to Generative AI (Design, development of GenAI application in production) Strong understanding of RAG, Vector Database, Lang Chain and multimodal AI applications. Strong understanding of deploying and optimizing AI application in production. Strong knowledge of statistical and data mining techniques like Linear & Logistic Regression analysis, Decision trees, Bagging, Boosting, Time Series and Nonparametric analysis. Strong knowledge of DL & Neural Network Architectures (CNN, RNN, LSTM, Transformers etc.) Strong knowledge of SQL and R/Python and experience with distribute data/computing tools/IDEs. Experience in advanced Text Analytics (NLP, NLU, NLG). Strong handson experience of endtoend statistical model development and implementation Understanding of LLMOps, ML Ops for scalable ML development. Basic understanding of DevOps and deployment of models into production (PyTorch, TensorFlow etc.). Expert level proficiency algorithm building languages like SQL, R and Python and data visualization tools like Shiny, Qlik, Power BI etc. Exposure to Cloud Platform (Azure or AWS or GCP) technologies and services like Azure AI/ Sage maker/Vertex AI, Auto ML, Azure Index, Azure Functions, OCR, OpenAI, storage, scaling etc. Technical Skills required (Any one or more) Experience in video/ image analytics (Computer Vision) Experience in IoT/ machine logs data analysis Exposure to data analytics platforms like Domino Data Lab, c3.ai, H2O, Alteryx or KNIME Expertise in Cloud analytics platforms (Azure, AWS or Google) Experience in Process Mining with expertise in Celonis or other tools Proven capability in using Generative AI services like OpenAI, Google (Gemini) Understanding of Agentic AI Framework (Lang Graph, Auto gen etc.) Understanding of finetuning for pretrained models like GPT, LLaMA, Claude etc. using LoRA, QLoRA and PEFT technique. Proven capability in building customized models from opensource distributions like Llama, Stable Diffusion Mandatory skill sets AI chatbots, Data structures, GenAI objectoriented programming, IDE, API, LLM Prompts, Streamlit Preferred skill sets AI chatbots, Data structures, GenAI objectoriented programming, IDE, API, LLM Prompts, Streamlit Years of experience required 36 Years Education qualification BE, B. Tech, M. Tech, M. Stat, Ph.D., M.Sc. (Stats / Maths) Education Degrees/Field of Study required Doctor of Philosophy, Bachelor of Engineering, Bachelor of Technology Degrees/Field of Study preferred Required Skills Chatbots, Data Structures, Generative AI Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, C++ Programming Language, Communication, Complex Data Analysis, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Machine Learning, Machine Learning Libraries, Named Entity Recognition, Natural Language Processing (NLP), Natural Language Toolkit (NLTK) {+ 20 more} Travel Requirements Government Clearance Required?

Why Join Us To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win. We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees passion for travel and ensure a rewarding career journey. We re building a more open world. Join us. Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge technology to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential to driving our success. Why Join Us To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated, and we believe that when one of us wins, we all win. We offer a full benefits package, including exciting travel perks, generous time off, parental leave, a global hybrid work setup (with some pretty cool offices), and career development resources. All of this is designed to fuel our employees passion for travel and ensure a rewarding career journey. We re building a more open world. Join us. About the role Are you passionate about data, analytics, and collaborating with top talent to tackle complex problemsIf youre motivated to make an immediate impact on reimagining travel through insightful recommendations that drive improvements, we want to speak with you! We are seeking an experienced analytics professional to join our AI Agent Product Analytics Team, supporting a portfolio of some of the world s leading online travel brands. This is a mid-level individual contributor role, partnering with product managers and focusing on user experience optimization via GenAI-driven personalization. As a Data Scientist, you ll collaborate with a multidisciplinary team to solve a wide range of problems. You will bring scientific rigor and statistical methods to the challenges of business growth and product development. This role supports key business decisions throughout the product development lifecycle to improve the user experience for millions of Expedia customers. You ll be responsible for uncovering customer friction points, hypothesis generation and prioritization, experiment design, unbiased test analysis, actionable recommendations, and product optimization. If you are a self-starter who has demonstrated success using analytics to drive innovation and user engagement, this role is for you. In this role you will Apply expertise in quantitative analysis, machine learning, data mining, and data visualization to improve customer experience and business outcomes, with a focus on impactful analytics Guide product teams to actionable insights Own end-to-end testing excellence, including evaluating A/B and multivariate (MVT) tests, identifying opportunities, and recommending new features for test-and-learn initiatives Evaluate and apply alternative methods to supplement randomized testing Develop metrics frameworks for your product; build accurate, user-friendly dashboards/reports; and collaborate on goal setting, performance reviews, and strategic planning Take initiative to identify current and potential problems and recommend optimal solutions based on trade-offs Experience and qualifications 4+ years of experience in quantitative analysis to solve business problems Bachelor s degree in a science, technology, engineering, or mathematics (STEM) field Strong analytical skills, with the ability to break down complex business scenarios Experience with large datasets and proficiency in SQL or programming languages such as R or Python Excellent communicator with the ability to tell compelling stories using data Solid understanding of statistics and hypothesis testing (e.g., confidence intervals, regression, time series, clustering, factor analysis) Experience with visualization tools (e.g., Tableau) Familiarity with Adobe Analytics or Google Analytics is a plus Detail-oriented with a strong curiosity and passion for making an impact Accommodation requests If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request . We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others. Expedia Groups family of brands includes: Brand Expedia , Hotels.com , Expedia Partner Solutions, Vrbo , trivago , Orbitz , Travelocity , Hotwire , Wotif , ebookers , CheapTickets , Expedia Group Media Solutions, Expedia Local Expert , CarRentals.com , and Expedia Cruises . 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50 Employment opportunities and job offers at Expedia Group will always come from Expedia Group s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs . Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.

Collaborate with engineers, product managers, and operations leaders to build predictive maintenance models, improve manufacturing throughput, and drive cost savings. Work on anomaly detection, quality control, and forecasting use cases within our IIoT platform. You will report to Lead Sr Solution Architect of the function and will work from our Electronics City, Bengaluru Office in Hybrid work model. Your Responsibilities: Design and implement scalable ETL pipelines and ML workflows using platforms like AzureML, AWS SageMaker. Develop and deploy time-series models for forecasting and anomaly detection. Apply classical ML techniques such as regression, decision trees, clustering, and deep learning to solve business problems. Collaborate with cross-functional teams to translate business requirements into data science solutions. Contribute to model monitoring, performance tuning, and continuous improvement. You will report to Lead Sr Solution Architect of the function and will work from our Electronics City, Bengaluru Office in Hybrid work model. The Essentials - You Will Have: 1 2 years of experience in data science or machine learning roles. Proven experience with cloud ML platforms (AzureML, SageMaker, or equivalent). Strong understanding and hands-on experience with time-series modeling and forecasting techniques. Solid foundation in classical ML algorithms (e.g., regression, decision trees, clustering, deep learning). Proficiency in Python, SQL, and ML libraries such as scikit-learn, TensorFlow, or PyTorch. Experience building and maintaining ETL pipelines for large-scale data processing. The Preferred - You Might Also Have: Familiarity with BI tools (Tableau, Looker, Power BI) and MLOps frameworks (MLflow, Kubeflow). Familiarity with FastAPI for building and deploying model serving endpoints. Familiarity working with in Linux Environments. What We Offer: Our benefits package includes Comprehensive mindfulness programs with a premium membership to Calm Volunteer Paid Time off available after 6 months of employment for eligible employees. Company volunteer and donation matching program Your volunteer hours or personal cash donations to an eligible charity can be matched with a charitable donation. Employee Assistance Program Personalized wellbeing programs through our OnTrack program On-demand digital course library for professional development At Rockwell Automation we are dedicated to building a diverse, inclusive and authentic workplace, so if youre excited about this role but your experience doesnt align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right person for this or other roles. #LI-Hybrid #LI-FR1 Rockwell Automation s hybrid policy aligns that employees are expected to work at a Rockwell location at least Mondays, Tuesdays, and Thursdays unless they have a business obligation out of the office.

We are eagerly seeking candidates with 3 to 12 years’ experience for a Data Scientist to join our dynamic team. The ideal candidate will play a pivotal role in data analysis, statistical modeling, and machine learning to extract valuable insights from data Role: Data Scientist Location: Pune/Hyderabad/Mumbai Experience: 3 to 12 years Job type: Full time Work type: Hybrid Impact you will realize: Job Responsibilities Individuals will be responsible for leveraging their expertise in data analysis, statistical modeling, and machine learning to extract valuable insights from data Conduct in-depth data analysis to identify trends, patterns and anomalies in large datasets using tools like Python, SQL. Develop solutions using Machine Learning and Generative AI Develop and apply statistical models to gain insights and make predictions based on historical data. Build, train and deploy machine learning models for various applications, such as predictive modeling, customer segmentation, demand/sales forecasting, predictive maintenance etc. Assess model performance, iterate on models and fine-tune hyperparameters to optimize predictive accuracy and generalization. Deploy machine learning models into production systems and make necessary updates or improvements. Ensure data privacy and compliance with relevant regulations Documentation of analytical methods, data pipelines, and model workflows Key skills you will require: Primary Skills Conduct in-depth data analysis to identify trends, patterns and anomalies in large datasets using tools like Python, SQL. Develop solutions using Machine Learning and Generative AI Develop and apply statistical models to gain insights and make predictions based on historical data. Build, train and deploy machine learning models for various applications, such as predictive modeling, customer segmentation, demand/sales forecasting, predictive maintenance etc. Assess model performance, iterate on models and fine-tune hyperparameters to optimize predictive accuracy and generalization. Deploy machine learning models into production systems and make necessary updates or improvements. Ensure data privacy and compliance with relevant regulations Documentation of analytical methods, data pipelines, and model workflows

Data Scientist- ( Lead) - J49417 Proficiency with Python (Pandas, NumPy), SQL, and Java. Experience with LLMs, LangChain, and Generative AI technologies. Familiarity with ML frameworks (TensorFlow, PyTorch) and data engineering tools (Spark, Kafka). Microservices, CI CD, ML Strong data analysis skills and ability to present findings to both technical and non-technical stakeholders. Proficient understanding of key data engineering concepts, such as data lakes, columnar formats, ETL tools, and BI tools. Knowledge in Machine Learning, NLP, Recommender systems, personalization, Segmentation, microservices architecture and API development. Ability to adapt to a fast-paced, dynamic work environment and learn new technologies quickly. Work in a team/ Independently. Excellent Written & Verbal Communication Skills Solid critical thinking and questioning skills. High degree of flexibility - willing to fill in the gaps rather than relying on others Strong communication skills, especially in presenting data insights. Flexibility, problem-solving, and a proactive approach in a fast-paced environment Qualification -BA,BBA,BBA/BMS,BBI,BCA,BCom,BCS,BDES,BE-Comp/IT,BEd,BE-Other,BFA,BFM,BIS,BIT,BMS,BSc-Comp/IT,BSc-Other,BTech-Comp/IT,BTech-Other,CA,CS,DCA,DCS,DE-Comp/IT,DE-Other,Diploma,ICWA,LLB, MA,MBA,MBBS, MCA,MCM,MCom,MCS,ME-Comp/IT,ME-Other,MIS,MIT,MMS,MSc-Comp/IT,MS-Comp/IT

Inviting applications for the role of Lead Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities Collaborate with cross-functional teams to identify, analyze, and interpret complex datasets to develop actionable insights and drive data-driven decision-making. Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Experience in data science, machine learning, AI applications, and generative AI modelling. Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills.

Job Description: We are looking for a talented and experienced Senior Data Scientist with a minimum of 4 years of professional experience in model development and expertise in Gen AI projects. As a Senior Data Scientist, you will be responsible for developing advanced machine learning models, conducting exploratory data analysis (EDA), performing feature selection/reduction, and utilizing cutting-edge technologies to deliver high-quality solutions. The ideal candidate should possess strong programming proficiency in Python and experience with cloud platforms like GCP or equivalent, as well as visualization tools like Qliksense, Power BI, Looker Studio, or Tableau. Job Responsibility: Data Scientists 4+ Year (Mandatory Skills) Model development (regression and classification), should have strong experience in performing EDA, Feature selection/Feature Reduction, building models and evaluate its performance Should have worked on Gen AI project Strong programming proficiency in python with mastery of data science libraries Pandas, numpy and scikitlearn GCP (BQ, Vertex AI) or other equivalent cloud Visualization (Qliksense / Looker Studio / Power BI / Tableau) Skills: GenAI Model development (regression and classification) EDA Python GCP / other equivalent cloud Visualization Data Scientist We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.

The Senior Data Science Engineer will leverage advanced data science techniques to solve complex business problems, guide decision-making processes, and mentor junior team members. This role requires a combination of technical expertise in data analysis, machine learning, and project management skills. Responsibilities Data Analysis and Modeling: Analyze large-scale telecom datasets to extract actionable insights and build predictive models for network optimization and customer retention. Conduct statistical analyses to validate models and ensure their effectiveness. Machine Learning Development: Design and implement machine learning algorithms for fraud detection, churn prediction, and network failure analysis. Telecom-Specific Analytics: Apply domain knowledge to improve customer experience by analyzing usage patterns, optimizing services, and predicting customer lifetime value. ETL Processes: Develop robust pipelines for extracting, transforming, and loading telecom data from diverse sources. Collaboration: Work closely with data scientists, software engineers, and telecom experts to deploy solutions that enhance operational efficiency. Data Governance: Ensure data integrity, privacy, security and compliance with industry standards Qualifications Advanced degree in Data Science, Statistics, Computer Science, or a related field. Extensive experience in data science roles with a strong focus on machine learning and statistical modeling. Proficiency in programming languages such as Python or R and strong SQL skills. Familiarity with big data technologies (e.g., Hadoop, Spark) is advantageous. Expertise in cloud platforms such as AWS or Azure.

Role Summary: We are looking for an accountable, multitalented candidate to facilitate the operations. The computer vision consultant must be able to develop, implement and deploy ML functions across functions. The candidate should be adept at leading and conducting independent project work using the state-of-the-art deep learning technology, as well as participate in the transfer of knowledge from research to industry. The consultant will also have to collaborate with internal team and clients, to ensure that their approach meets the needs of each project. He/she should be able to deliver results according to project schedules while maintaining quality standards. The candidate will also be responsible to contribute towards organizational initiatives. Job Requirement Job Responsibilities: 1. Substantial hands-on experience with data handling. Capable of managing large volumes of data, extract, clean and comprehend 2. Able to analyze data independently and draw out salient insights. Able to define workflow for oneself and associates on a daily or periodic basis, contingent on the requirements of the project 3. Able to contribute meaningfully to brainstorming discussions around nuances of the project 4. Skilled in CNN or RNN or Feed Forward/ Back Propagation Network and Hyperparameter Tuning 5. Good Knowledge on Natural Knowledge Processing, Verbatim Analysis & Speech to Text / vice versa using few alternate approaches / techniques 6. Comfortable with statistical procedures, such as basic distributions, regressions, logistic models 7. Experience with advanced statistics and Machine Learning algorithms is a plus 8. Developing comprehensible analytical solutions to solve business problems using domain knowledge or 9. statistical procedures depending on the requirements of the project 10. Comfortable in representing the proceedings and/or findings in a power-point 11. Comfortable in mentoring junior resources, and creating an environment of learning in the team 12. Helping the company with Business Development initiatives such as sales collaterals, PoCs, Case Studies 13. Develop and define an area of expertise and take relevant trainings on the same for the organization 14. Contribute to org level activities, such as taking interviews 15. Work with team to estimate work effort 16. Understand the work methodology and be an active participant in strengthening the team 17. Liaising with coworkers and clients on several projects 18. Commitment to learning and continuous improvement 19. The candidate should be able to work under tight timelines with minimal supervision

Job Responsibilities: Substantial hands-on experience with data handling. Capable of managing large volumes of data, extract, clean and comprehend Experience with advanced statistics and Machine Learning algorithms like: Linear Regression, Logistic Regression, Tree-Based Models Experience with model deployment Experience with recommendation models, such as content-based filtering, collaborative filtering, and hybrid models. Knowledge of visualization tools such as POWER BI, Tableau is a plus. Hands on knowledge of end to end model development with code modularization. Hands on knowledge of SQL/PostgreSQL/Snowflake/DBT with understanding of CTEs, Joins, Window Functions, Aggregation Industry knowledge of Retail/E-commerce/Marketing is a plus. Developing comprehensible analytical solutions to solve business problems using domain knowledge or statistical procedures depending on the requirements of the project Comfortable in representing the proceedings and/or findings in a power-point Comfortable in mentoring junior resources, and creating an environment of learning in the team Helping the company with Business Development initiatives such as sales collaterals, PoCs, Case Studies Develop and define an area of expertise and take relevant trainings on the same for the organization The candidate should be able to work under tight timelines with minimal supervision Job Requirement EXPERTISE AND QUALIFICATIONS Experience: 4 to 7 Years Location: Bengaluru - Hybrid (HSR Layout Office) Must Have: • Statistics • Machine Learning • Python • SQL Good to Have: • PowerPoint & Excel

Job Title - Retail Specialized Data Scientist Level 9 SnC GN Data & AI Management Level:09 - Consultant Location:Bangalore / Gurgaon / Mumbai / Chennai / Pune / Hyderabad / Kolkata Must have skills: A solid understanding of retail industry dynamics, including key performance indicators (KPIs) such as sales trends, customer segmentation, inventory turnover, and promotions. Strong ability to communicate complex data insights to non-technical stakeholders, including senior management, marketing, and operational teams. Meticulous in ensuring data quality, accuracy, and consistency when handling large, complex datasets. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Strong proficiency in Python for data manipulation, statistical analysis, and machine learning (libraries like Pandas, NumPy, Scikit-learn). Expertise in supervised and unsupervised learning algorithms Use advanced analytics to optimize pricing strategies based on market demand, competitor pricing, and customer price sensitivity. Good to have skills: Familiarity with big data processing platforms like Apache Spark, Hadoop, or cloud-based platforms such as AWS or Google Cloud for large-scale data processing. Experience with ETL (Extract, Transform, Load) processes and tools like Apache Airflow to automate data workflows. Familiarity with designing scalable and efficient data pipelines and architecture. Experience with tools like Tableau, Power BI, Matplotlib, and Seaborn to create meaningful visualizations that present data insights clearly. Job Summary : The Retail Specialized Data Scientist will play a pivotal role in utilizing advanced analytics, machine learning, and statistical modeling techniques to help our retail business make data-driven decisions. This individual will work closely with teams across marketing, product management, supply chain, and customer insights to drive business strategies and innovations. The ideal candidate should have experience in retail analytics and the ability to translate data into actionable insights. Roles & Responsibilities: Leverage Retail Knowledge:Utilize your deep understanding of the retail industry (merchandising, customer behavior, product lifecycle) to design AI solutions that address critical retail business needs. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Apply machine learning algorithms, such as classification, clustering, regression, and deep learning, to enhance predictive models. Use AI-driven techniques for personalization, demand forecasting, and fraud detection. Use advanced statistical methods help optimize existing use cases and build new products to serve new challenges and use cases. Stay updated on the latest trends in data science and retail technology. Collaborate with executives, product managers, and marketing teams to translate insights into business actions. Professional & Technical Skills : Strong analytical and statistical skills. Expertise in machine learning and AI. Experience with retail-specific datasets and KPIs. Proficiency in data visualization and reporting tools. Ability to work with large datasets and complex data structures. Strong communication skills to interact with both technical and non-technical stakeholders. A solid understanding of the retail business and consumer behavior. Programming Languages:Python, R, SQL, Scala Data Analysis Tools:Pandas, NumPy, Scikit-learn, TensorFlow, Keras Visualization Tools:Tableau, Power BI, Matplotlib, Seaborn Big Data Technologies:Hadoop, Spark, AWS, Google Cloud Databases:SQL, NoSQL (MongoDB, Cassandra) Additional Information: - Qualification Experience: Minimum 3 year(s) of experience is required Educational Qualification: Bachelors or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.

Job Title - + + Management Level: Location:Kochi, Coimbatore, Trivandrum Must have skills:Big Data, Python or R Good to have skills:Scala, SQL Job Summary A Data Scientist is expected to be hands-on to deliver end to end vis a vis projects undertaken in the Analytics space. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. Roles and Responsibilities Identify valuable data sources and collection processes Supervise preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns for insurance industry. Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Collaborate with engineering and product development teams Hands-on knowledge of implementing various AI algorithms and best-fit scenarios Has worked on Generative AI based implementations Professional and Technical Skills 3.5-5 years experience in Analytics systems/program delivery; at least 2 Big Data or Advanced Analytics project implementation experience Experience using statistical computer languages (R, Python, SQL, Pyspark, etc.) to manipulate data and draw insights from large data sets; familiarity with Scala, Java or C++ Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications Hands on experience in Azure/AWS analytics platform (3+ years) Experience using variations of Databricks or similar analytical applications in AWS/Azure Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop) Strong mathematical skills (e.g. statistics, algebra) Excellent communication and presentation skills Deploying data pipelines in production based on Continuous Delivery practices. Additional Information Multi Industry domain experience Expert in Python, Scala, SQL Knowledge of Tableau/Power BI or similar self-service visualization tools Interpersonal and Team skills should be top notch Nice to have leadership experience in the past Qualification Experience:3.5 -5 years of experience is required Educational Qualification:Graduation (Accurate educational details should capture)

At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities,collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client"s challenges of today and tomorrow.Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose. Your role As a Senior Data Scientist, you are expected to develop and implement Artificial Intelligence based solutions across various disciplines for the Intelligent Industry vertical of Capgemini Invent. You are expected to work as an individual contributor or along with a team to help design and develop ML/NLP models as per the requirement. You will work closely with the Product Owner, Systems Architect and other key stakeholders right from conceptualization till the implementation of the project. You should take ownership while understanding the client requirement, the data to be used, security & privacy needs and the infrastructure to be used for the development and implementation. The candidate will be responsible for executing data science projects independently to deliver business outcomes and is expected to demonstrate domain expertise, develop, and execute program plans and proactively solicit feedback from stakeholders to identify improvement actions. This role requires a strong technical background, excellent problem-solving skills, and the ability to work collaboratively with stakeholders from different functional and business teams. The role also requires the candidate to collaborate on ML asset creation and eager to learn and impart trainings to fellow data science professionals. We expect thought leadership from the candidate, especially on proposing to build a ML/NLP asset based on expected industry requirements. Experience in building Industry specific (e.g. Manufacturing, R&D, Supply Chain, Life Sciences etc), production ready AI Models using microservices and web-services is a plus. Programming Languages Python NumPy, SciPy, Pandas, MatPlotLib, Seaborne Databases RDBMS (MySQL, Oracle etc.), NoSQL Stores (HBase, Cassandra etc.) ML/DL Frameworks SciKitLearn, TensorFlow (Keras), PyTorch, Big data ML Frameworks - Spark (Spark-ML, Graph-X), H2O Cloud Azure/AWS/GCP Your Profile Predictive and Prescriptive modelling using Statistical and Machine Learning algorithms including but not limited to Time Series, Regression, Trees, Ensembles, Neural-Nets (Deep & Shallow CNN, LSTM, Transformers etc.). Experience with open-source OCR engines like Tesseract, Speech recognition, Computer Vision, face recognition, emotion detection etc. is a plus. Unsupervised learning Market Basket Analysis, Collaborative Filtering, Dimensionality Reduction, good understanding of common matrix decomposition approaches like SVD. Various Clustering approaches Hierarchical, Centroid-based, Density-based, Distribution-based, Graph-based clustering like Spectral. NLP Information Extraction, Similarity Matching, Sentiment Analysis, Text Clustering, Semantic Analysis, Document Summarization, Context Mapping/Understanding, Intent Classification, Word Embeddings, Vector Space Models, experience with libraries like NLTK, Spacy, Stanford Core-NLP is a plus. Usage of Transformers for NLP and experience with LLMs like (ChatGPT, Llama) and usage of RAGs (vector stores like LangChain & LangGraps), building Agentic AI applications. Model Deployment ML pipeline formation, data security and scrutiny check and ML-Ops for productionizing a built model on-premises and on cloud. Required Qualifications Masters degree in a quantitative field such as Mathematics, Statistics, Machine Learning, Computer Science or Engineering or a bachelors degree with relevant experience. Good experience in programming with languages such as Python/Java/Scala, SQL and experience with data visualization tools like Tableau or Power BI. Preferred Experience Experienced in Agile way of working, manage team effort and track through JIRA Experience in Proposal, RFP, RFQ and pitch creations and delivery to the big forum. Experience in POC, MVP, PoV and assets creations with innovative use cases Experience working in a consulting environment is highly desirable. Presupposition High Impact client communication The job may also entail sitting as well as working at a computer for extended periods of time. Candidates should be able to effectively communicate by telephone, email, and face to face. What you will love about working here We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance. At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities. Equip yourself with valuable certifications in the latest technologies such as Generative AI.

Junior Data Scientist Job Description As a Junior Data Scientist working at TTEC Digital, you will work on a team with diverse clients and industries to create data-driven solutions, develop cutting edge algorithms and provide expert insights to increase our understanding of customer behavior and needs. We are looking for someone with a strong foundation in data science, excellent analytical skills, and a passion for solving complex problems. Key Responsibilities: Assist in collecting, cleaning, and preprocessing data from various sources. Perform exploratory data analysis to uncover trends, patterns, and anomalies. Develop and implement statistical models and machine learning algorithms to address business challenges. ¢ ¢ ¢ Generate and interpret reports, visualizations, and dashboards to communicate findings to stakeholders. Collaborate with cross-functional teams to understand business requirements and deliver data- driven solutions. Stay updated with the latest developments in data science and machine learning technologies. Qualifications: ¢ ¢ Graduated in Engineering or related field in the last 2 years Prior professional work experience (maximum of 2 years) is preferred. Extra preference if the experience is in Data Science domain ¢ If the candidate does not possess relevant work experience, they should have completed online/offline Data Science programs with at least 6 months duration Proficiency in programming languages such as Python, SQL, Pandas, PySpark. Experience with data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib, Tableau, Power BI). ¢ ¢ ¢ ¢ ¢ ¢ Basic understanding of statistical methods and machine learning algorithms. Strong analytical and problem-solving skills with attention to detail. Ability to work independently and collaboratively in a team environment. Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders. TTEC Digital Analytics India SALARPURIA SATTVA KNOWLEDGE CITY, HITEC City, Hyderabad, Telangana 500081

Description Lang chain expert skilled in python for creating new chains or fixing existing ones, also leverage ML or Gen AI models for data extraction Must Have Programming Proficiency: Especially in Python (NumPy, Pandas, Scikit-learn), and optionally R or Java Machine Learning Algorithms: Supervised, unsupervised, and ensemble methods (e.g., decision trees, SVMs, XGBoost) Deep Learning: Understanding of neural networks, CNNs, RNNs using frameworks like TensorFlow or PyTorch Data Handling & Preprocessing: Cleaning, transforming, and visualizing large datasets Gen AI, Open AI, AI Search Version Control: Git/GitHub for collaboration and reproducibility Problem Solving & Critical Thinking: Ability to frame business problems as data science tasks. Good to Have Data Lake (Microsoft SQL Server, Azure Cosmos, Azure Data Lake) Cloud Computing

Career Area: Technology, Digital and Data Job Description: Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. A Data Scientist is responsible for supporting freight analytics/forecasting for process partners by leveraging suitable software. This position is in Bangalore and reports to the Analytics Manager responsible for this area. A person in this role is expected to support 1-2 projects at a time and guide the other team members in work related queries. JOB DUTIES: The job duties of a Data Scientist are to support/lead projects in the domain of freight analytics. To be successful, he/she must utilize technical skills as well as soft skills. The domain and technical skills are defined in 4 key skills: Domain (logistics/freight/supply chain) knowledge, technical (SAS, SQL, MS Office suite) knowledge, data purification (ETL) & analysis and building insights for customer review. It would be added advantage to have working knowledge of visualization tools like Tableau and/or Power BI. This role also will support technology solutions for the analytics team and meeting the needs of the organization. In this role one is expected to identify and drive continuous improvement within the department. In addition to technical skills, a Data Scientist needs to demonstrate intermediate to fully skilled levels of the following values-based competencies (VBCs): integrity & trust; building inclusive relationships; customer focus; problem solving; priority setting; and dealing with uncertainty. Although the requirements above describe most of the responsibilities of the Data Scientist, due to the breadth of issues that arise on projects, it is sometimes expected that he/she takes on other responsibilities outside of this job description. Background/Experience (Required): Bachelor’s degree in engineering, supply chain management, logistics or a related field. Require 3 - 6 years of relevant experience in either of the following fields - supply chain planning, transportation/inventory optimization & simulation. Good knowledge on SAS with one or more successful projects completed by the individual. Must be comfortable working in MS Office, and industry standard statistics and data visualization packages. Excellent communication and presentation skills. Good analytical thinker, experience in data analysis and project management, ability to work well in team settings, with attention to detail. This position requires working onsite five days a week Background/Experience (Desired): Bachelor or Master degree in Operations Research, college degree in supply chain, logistics, or industrial engineering (operation research). Basic level knowledge of any one of the supply chain optimization tools (BY Transportation Modeler, Supply Chain Guru, IBM LogicNet, ILOG CPLEX, Anylogistics) Proficient in Microsoft Office (Excel, Access, PowerPoint, Word) Experience with visualization tools like Tableau or Power BI Skill Descriptors Programming Languages: Knowledge of basic concepts and capabilities of SQL/SAS/Python programming; ability to use tools, techniques and platforms in order to write and modify programming languages. Level Basic Understanding: Describes the basic concepts of programming and program construction activities. Uses programming documentation including program specifications in order to maintain standards. Describes the capabilities of major programming languages. Identifies locally relevant programming tools. Query and Database Access Tools: Knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use. Level Basic Understanding: Identifies query facilities that are available in one's own environment. Explains organization's standards, procedures and practices for building queries. Describes the functions and features of query and database access tools. Identifies the key benefits and drawbacks of query languages. Business Statistics: Knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions. Level Basic Understanding: Identifies and describes basic statistical measures. Summarizes the underlying uncertainties associated with statistical analysis and reporting. Accuracy and Attention to Detail: Understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision. Level Working Knowledge: Accurately gauges the impact and cost of errors, omissions, and oversights. Utilizes specific approaches and tools for checking and cross-checking outputs. Processes limited amounts of detailed information with good accuracy. Learns from mistakes and applies lessons learned. Develops and uses checklists to ensure that information goes out error-free. Analytical Thinking: Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems. Level Basic Understanding: Names specific tools or techniques that can be used to support the analytical thinking process. Describes specific software applications or products used for business analytics. Gives examples of how analytical thinking has been used to resolve problems. Additional Info: This position will require travelling about 10% of the time. Caterpillar is not currently hiring individuals for this position who now or in the future require sponsorship for employment visa status; however, as a global company, Caterpillar offers many job opportunities outside of Singapore which can be found through our employment website at www.caterpillar.com/careers. What You Will Get: Our goal at Caterpillar is for you to have a rewarding career. Our teams are critical to the success of our customers who build a better world. Here you earn more than just wage, because we value your performance, we offer a total rewards package that provides day one benefits along with the potential of a variable bonus. Additional benefits include paid annual leave, flexi leave, medical and insurance (prorated based upon hire date). Final Details: Please frequently check the email associated with your application, including the junk/spam folder, as this is the primary correspondence method. If you wish to know the status of your application – please use the candidate log-in on our career website as it will reflect any updates to your status. About Caterpillar Caterpillar Inc. is the world’s leading manufacturer of construction and mining equipment, off-highway diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. For nearly 100 years, we’ve been helping customers build a better, more sustainable world and are committed and contributing to a reduced-carbon future. Our innovative products and services, backed by our global dealer network, provide exceptional value that helps customers succeed. Posting Dates: July 18, 2025 - July 24, 2025 Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply Not ready to apply? Join our Talent Community.

The Fixed Income Reference team collects, manages, and supplies content related to Bonds . This content is used extensively across by clients and beyond Refinitiv/LSEG and is a critical asset to a wide range of Refinitiv/LSEG products. The role of the Data Scientist is to: Design and develop new methodologies, quantitative models, analysis and commentary (as relevant) that enhance existing or new processes. Maintain existing product performance and independent analysis standards. Internally, work with various departments to grow new ideas and expand the scope of existing products. Essential Day-to-Day Responsibilities: Data handling, data processing and programming Develop automated solutions for sourcing/loading Fixed Income Reference data into Database Analyze Fixed Income Reference content to establish patterns/trends Develop, improve and run quantitative models Generate solutions through AI & machine learning for core processes Work with business, content and product groups for large-scale analytics problems Build POCs, visualizations and pipeline tools for product design and development Work with development groups for deployment of analytics solutions Interact with other internal teams as needed, with supervision. Knowledge & Skills: Understanding of algorithms, model building, and evaluation Strong understanding of machine learning algorithms Knowledge of neural networks and deep learning frameworks Extensive experience using Python or R or equivalent Skills in transforming and preparing data for model training Proficient in using tools and libraries such as scikit-learn, numpy, pandas and jupyter Solid relational database skills Solid understanding of statistics and statistical language such as R Ability to handle large quantities of data Narrate stories (to technical and mostly non-technical audience) about our content and processes by data analysis and visualization Strong written, communication and presentation skills. Able to respond and present work to peers, senior management and other stakeholders Qualification: Higher education in Statistics, Mathematics or Engineering in Computer Science with Data science certification LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth. Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership , Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions. Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce. You will be part of a collaborative and creative culture where we encourage new ideas and are committed to sustainability across our global business. You will experience the critical role we have in helping to re-engineer the financial ecosystem to support and drive sustainable economic growth. Together, we are aiming to achieve this growth by accelerating the just transition to net zero, enabling growth of the green economy and creating inclusive economic opportunity. LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives. We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it’s used for, and how it’s obtained, your rights and how to contact us as a data subject. If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.