3292 Data Scientist Jobs - Page 6

Role Description : As a Technical Lead - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Technical Lead - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Technical Lead - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Software Engineer - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Qualifications 3-5 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers. Responsibilities Utilize your expertise in online scraping techniques to gather and process data from various sources. Apply advanced machine learning and AI algorithms to clean, structure, and analyse complex datasets. Collaborate with our team to develop and deploy scalable data solutions. Contribute to the optimization of our data infrastructure and analytics pipelines. Generate actionable insights for business improvements Qualifications Bachelor's or Master's degree in quantitative field (Data Science, Statistics, Mathematics, Computer Science, etc.). At least 5 years of experience in data science roles, preferably within the financial and/or life sciences industry. Deep understanding of predictive modelling, machine-learning, clustering and classification techniques, and algorithms. Fluency in programming languages commonly used in data science (at least Python). Fluency in using AI code editors like Windsurf / Cursor. Familiarity with Java is a plus. Strong understanding of machine learning techniques, with experience implementing models of varying complexity. Ability to work independently and manage multiple projects simultaneously. Excellent communication skills and a collaborative mindset.

- Hands on working experience in Python. - Experience with data visualization libraries. - Strong working experience grasp of DS stack packages. - Basic to intermediate SQL. - Experience working with GCP. - Hands-on experience deploying ML solutions.

The Role Develops and program methods, automated processes, and systems to cleanse, integrate and analyze structured and unstructured, diverse big data sources to generate actionable insights and solutions using machine learning and advanced analytics . Interprets and communicates insights and findings from analyses and experiments to other analysts, data scientists, team members and business partners. The Main Responsibilities Support the development of end-to-end analytics solutions by assisting in the design and implementation of solutions that cover the entire data science lifecycle, including data discovery, cleaning, exploratory data analysis, model building, and deployment. Assist with operationalizing models and participate in the iterative process of refining models and insights based on feedback and business requirements. Analyze data and build predictive, prescriptive, and advanced analytical models in various areas including capacity planning, effect/anomaly detection, predictive asset failure/maintenance, workload optimization, customer segmentation and business performance. Gain direct experience with various modeling techniques such as clustering, regression, and time series forecasting, applying these techniques to generate actionable insights and recommendations. Mine information for previously unknown patterns and insights hidden in these assets and leverage them for competitive advantage. Create compelling data visualizations and dashboards to effectively communicate findings to both technical and non-technical audiences. Present insights in a clear, concise, and actionable manner. Collaborate within and across cross-functional teams, working closely with data engineers, data scientists, and business stakeholders to understand business problems, gather requirements, and communicate insights effectively. Contribute to collaborative problem-solving sessions and agile development processes. Develop and operationalize end-to-end machine learning pipelines on Databricks , including feature engineering, model training, evaluation, and deployment. Implement and manage MLOps practices , integrating Git for version control, CI/CD pipelines for model deployment, and automated monitoring of models in production. Develop and consume RESTful APIs for data integration , enabling seamless connectivity between analytics applications and external systems. Ensure reproducibility, auditability, and governance of data science models by adhering to enterprise MLOps standards and frameworks. Support analytics democratization by packaging models as reusable components and APIs for consumption across the enterprise. What We Look for in a Candidate Able to apply techniques such as classification, clustering, regression, deep learning, association, anomaly detection, time series forecasting, Hidden Markov models and Bayesian inference to solve pragmatic business problems. Able to design working models and implement them on Big Data systems using Map Reduce or Spark frameworks . Familiar with Hadoop, Pig, Hive, Scope, Cosmos, or similar technologies . Able to work within an agile, iterative DevOps development process. Experience: 3+ years of experience delivering Machine Learning and Advanced Analytics solutions Experience with statistical programming environments like Python, R, SPSS, or IBM Watson Studio Experience building data models and performing complex queries using SQL Experience performance tuning large datasets Experience building large data pipelines and/or web services Experience developing visualization and dashboards using PowerBI or similar tools Fluent in one or more object-oriented languages like C#, C++, Scala, Java, and scripting languages like Python or Ruby "We are an equal opportunity employer committed to fair and ethical hiring practices. We do not charge any fees or accept any form of payment from candidates at any stage of the recruitment process. If anyone claims to offer employment opportunities in our company in exchange for money or any other benefit, please treat it as fraudulent and report it immediately."

• Collaborate with cross-functional teams, including data scientists and product managers, to acquire, process, and manage data for AI/ML model integration and optimization. • Design and implement robust, scalable, and enterprise-grade data pipelines to support state-of-the-art AI/ML models. • Debug, optimize, and enhance machine learning models, ensuring quality assurance and performance improvements. • Operate container orchestration platforms like Kubernetes, with advanced configurations and service mesh implementations, for scalable ML workload deployments. • Design and build scalable LLM inference architectures, employing GPU memory optimization techniques and model quantization for efficient deployment. • Engage in advanced prompt engineering and fine-tuning of large language models (LLMs), focusing on semantic retrieval and chatbot development. • Document model architectures, hyperparameter optimization experiments, and validation results using version control and experiment tracking tools like MLflow or DVC. • Research and implement cutting-edge LLM optimization techniques, such as quantization and knowledge distillation, ensuring efficient model performance and reduced computational costs. • Collaborate closely with stakeholders to develop innovative and effective natural language processing solutions, specializing in text classification, sentiment analysis, and topic modeling. • Stay up-to-date with industry trends and advancements in AI technologies, integrating new methodologies and frameworks to continually enhance the AI engineering function. • Contribute to creating specialized AI solutions in healthcare, leveraging domain-specific knowledge for task adaptation and deployment. QUALIFICATION Minimum education: Bachelors degree in any Engineering Stream Specialized training, certifications, and/or other special requirements: Nice to have Preferred education: Computer Science/Engineering. EXPERIENCE Minimum relevant experience - 4+ years in AI Engineering SKILLS AND COMPETENCIES Technical Skills: • Advanced proficiency in Python with expertise in data science libraries (NumPy, Pandas, scikit-learn) and deep learning frameworks (PyTorch, TensorFlow) • Extensive experience with LLM frameworks (Hugging Face Transformers, LangChain) and prompt engineering techniques • Experience with big data processing using Spark for large-scale data analytics • Version control and experiment tracking using Git and MLflow • Software Engineering & Development: Advanced proficiency in Python, familiarity with Go or Rust, expertise in microservices, test-driven development, and concurrency processing. • DevOps & Infrastructure: Experience with Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), and container orchestration (Kubernetes) with Helm and service mesh implementations. • LLM Infrastructure & Deployment: Proficiency in LLM serving platforms such as vLLM and FastAPI, model quantization techniques, and vector database management. • MLOps & Deployment: Utilization of containerization strategies for ML workloads, experience with model serving tools like TorchServe or TF Serving, and automated model retraining. • Cloud & Infrastructure: Strong grasp of advanced cloud services (AWS, GCP, Azure) and network security for ML systems. • LLM Project Experience: Expertise in developing chatbots, recommendation systems, translation services, and optimizing LLMs for performance and security. • General Skills: Python, SQL, knowledge of machine learning frameworks (Hugging Face, TensorFlow, PyTorch), and experience with cloud platforms like AWS or GCP. • Experience in creating LLD for the provided architecture. • Experience working in microservices based architecture. Domain Expertise: • Strong mathematical foundation in statistics, probability, linear algebra, and optimization • Deep understanding of ML and LLM development lifecycle, including fine-tuning and evaluation • Expertise in feature engineering, embedding optimization, and dimensionality reduction • Advanced knowledge of A/B testing, experimental design, and statistical hypothesis testing • Experience with RAG systems, vector databases, and semantic search implementation • Proficiency in LLM optimization techniques including quantization and knowledge distillation • Understanding of MLOps practices for model deployment and monitoring Professional Competencies: • Strong analytical thinking with ability to solve complex ML challenges • Excellent communication skills for presenting technical findings to diverse audiences • Experience translating business requirements into data science solutions • Project management skills for coordinating ML experiments and deployments • Strong collaboration abilities for working with cross-functional teams • Dedication to staying current with latest ML research and best practices • Ability to mentor and share knowledge with team members Role & responsibilities Preferred candidate profile

Introduction A career in IBM Software means you’ll be part of a team that transforms our customer’s challenges into solutions. Seeking new possibilities and always staying curious, we are a team dedicated to creating the world’s leading AI-powered, cloud-native software solutions for our customers. Our renowned legacy creates endless global opportunities for our IBMers, so the door is always open for those who want to grow their career. IBM’s product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive Your Role And Responsibilities The Data Scientist role requires a highly analytical individual proficient in Python programming, database management, and data science methodologies. You’ll focus on extracting insights from data, developing and implementing machine learning models, managing big data infrastructure, and supporting AI-driven product development. Key Responsibilities Data Collection and Cleansing: Collect and cleanse data from diverse sources to ensure high-quality datasets for decision-making. Data Exploration and Visualization: Explore and visualize data using advanced techniques to uncover insights and trends. Statistical Analysis: Apply statistical and mathematical techniques to provide robust analytical foundations for predictive modeling. Machine Learning and Deep Learning: Develop and implement machine learning and deep learning models to address business challenges. ML-Ops / AI-Ops: Demonstrate expertise in ML-Ops / AI-Ops practices to ensure efficient model deployment and management. Big Data Management: Manage big data infrastructure and execute data engineering tasks for efficient data processing. Version Control and Collaboration: Utilize version control systems like Git for maintaining codebase integrity and fostering collaboration. AI-Driven Product Development: Design, create, and support AI-driven products to deliver impactful solutions aligned with user needs and business objectives. Preferred Education Master's Degree Required Technical And Professional Expertise Industry Experience: Minimum of 5 years of experience in the IT industry, with a focus on data science and AI, specifically in implementing data-driven solutions Technical Proficiency: Proficient in Python programming, NLP techniques, and AI Frameworks (e.g., Hugging Face). Knowledge of common machine learning algorithms and frameworks: linear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Database Management: Knowledge of SQL and NoSQL database management. Data Science Skills: Strong background in data science, statistics, mathematics, and analytical techniques. Machine Learning Expertise: Expertise in machine learning and deep learning methodologies, including foundation models. Preferred Technical And Professional Experience Deep Learning Experience: Hands-on experience in data science for 5+ years with a minimum of 4 years in deep learning. Big Data Technologies: Familiarity with big data technologies and data engineering practices. Familiarity with MLOps practices and tools (e.g., MLflow, Airflow). Cloud Computing Experience: Experience with cloud computing platforms (AWS/Azure/Google/IBM) for leveraging advanced cloud-based services.

Job Characteristics: Demonstrates ability to extensively use and apply data science principles, methods, theories, and concepts to assignments where precedents may not exist. Demonstrates working knowledge and interconnectivity of other related disciplines. Provides solutions to a wide range of difficult problems through design and execution of data science research. Demonstrates ability and initiative to identify, experiment and collaborate on novel approaches to data science solutions. Makes significant contributions to the exploration, refinement and deployment of data science solutions. Education/Work Experience:Degree or advanced degree in data science, mathematics, statistics, computer science or related field. BS and 8-10 years related experience or MS and 5 years related experience or PhD and less than 2 years experience. Independence level/Reports to: Provides basic leadership and individually contributes to key data science projects/experiments of moderate scope and complexity with high impact on the business. Acts with considerable latitude in determining technical approach required to meet desired objectives. Normally reports to Director, Data Science Manager, or senior technical leader.

Job Description The Lead Data Scientist will deliver on activities related to the strategy, design, development, implementation of Data Science, Artificial Intelligence (AI) and Machine Learning (ML) for enterprise application functions. Frequently interacting with key stakeholders, the Data Scientist will lead and create advanced analytics models from conceptualization to completion. This position will support different products or lines of businesses to build innovations around AI. Responsibilities Collaborate with business functions/stakeholders on discovery for data science idea generation, provide ideas and influence as well as drive changes End-to-end ownership of work from ideation to production. Develop, manage and maintain Machine Learning and Deep Learning infrastructure from pipelines and modelling to machine learning products and decision support. Work with the business to understand the problem space, identify the opportunities, and translate our problems into analytical solutions Work with other Data Teams and Data Engineers to build upon our data collection, storage, and processing infrastructure Develop, distribute, support - standards, best practices, innovative and automation modeling techniques, and procedures Manage activities that take place during solution ideation, solution design, solution implementation, optimization, and operation Coordinate enhancements and maintenance of information systems to ensure highly reliable and cost-effective operation Qualifications 5+ years of Digital/Data/Analytics/Statistics experience, including 3+ years in Applied AI/ML and Data Science Design and conduct experiments, collect the data necessary to perform statistical hypothesis testing, and create inferences and recommendations Hands on experience in building Machine Learning-enabled products or working with large complex data sets Hands on working knowledge in ML techniques including classification, clustering, dimension reduction, regression, NLP, time series forecasting, and boosting to build explanatory, predictive, and prescriptive models appropriate for solving different problems Hands on experience with distributed data/computing and orchestration tools: Azure Databricks, Spark, MySQL etc. Hands on expertise with statistical techniques and their applications in business. Hands on coding experience with several languages: Python, JavaScript, Java, R etc. Experience with design and development of Generative AI models using state-of-the-art techniques Strategic planning experience that adapts to communication between technical and business stakeholders Strong verbal and written communication skills, interpersonal skills, and organizational skills Strong presentation skills with both technical and non-technical audiences Strong team leadership and/or project management experience with multiple simultaneous initiatives Skilled in the management of complex systems and decision-making under uncertainty Excellent time management skills and strong attention to detail, with experience in adhering to best practices of managing the life cycle of data-intensive ML projects About The Team At Wesco, we build, connect, power and protect the world. As a leading provider of business-to-business distribution, logistics services and supply chain solutions, we create a world that you can depend on. Our Company’s greatest asset is our people. Wesco is committed to fostering a workplace where every individual is respected, valued, and empowered to succeed. We promote a culture that is grounded in teamwork and respect. With a workforce of over 20,000 people worldwide, we embrace the unique perspectives each person brings. Through comprehensive benefits and active community engagement, we create an environment where every team member has the opportunity to thrive. Learn more about Working at Wesco here and apply online today! Founded in 1922 and headquartered in Pittsburgh, Wesco is a publicly traded (NYSE: WCC) FORTUNE 500® company. Wesco International, Inc., including its subsidiaries and affiliates (“Wesco”) provides equal employment opportunities to all employees and applicants for employment. Employment decisions are made without regard to race, religion, color, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, or other characteristics protected by law. US applicants only, we are an Equal Opportunity Employer. Los Angeles Unincorporated County Candidates Only: Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act.

About the Role We are looking for an experienced Data Scientist with expertise in Machine Learning, Generative AI, and Large Language Models (LLMs) to design, build, and deploy AI-driven solutions using the Azure ecosystem . Responsibilities Build end-to-end ML pipelines (data prep, training, validation, deployment). Apply LLMs & GenAI for NLP, predictive modeling, and analytics. Develop recommendation engines, scoring systems, and predictive models . Run A/B tests and apply statistical methods to optimize performance. Integrate ML solutions into business systems in collaboration with cross-functional teams. Skills & Experience 5+ years in ML/Data Science with strong Python skills. Hands-on with LLMs, GenAI frameworks, and deep learning (PyTorch/TensorFlow) . Experience with Azure ML, Cognitive Services, and Databricks . Knowledge of MLOps/model management (Azure ML Service / MLflow). Strong background in statistical evaluation and large-scale data handling .

ABOUT CUBASTION Cubastion Consulting Pvt. Ltd. is a prominent consulting firm that specializes in providing comprehensive business solutions to its clients. With a focus on delivering high-quality digital transformation services, fostering innovation and growth, building strong client relationships, and achieving sustainable success with delivery certainty, Cubastion Consulting sets itself apart as a leading player in the market. Our superpower is people, who help drive delivery success across the following focus areas. Digital Transformation | Performance Assurance | Process Excellence | Tech-Driven Engagements | Complex Solutions | Large Volumes At Cubastion Consulting, our primary objective is to deliver tailored and impactful solutions that address each client's unique needs and challenges. We firmly believe that excellence is achieved through meticulous research, the utilization of industry best practices, and the expertise of seasoned consultants. LOCATION Gurgaon (travel readiness outside home residence is important) EXPERIENCE 8+ years. ROLES & RESPONSIBILITIES: • Lead the architecture and deployment of LLM and GenAI-based applications. • Fine-tune and optimize state-of-the-art LLMs including GPT, LLaMA, Claude, Mistral, etc. • Design and implement advanced prompt engineering and Retrieval-Augmented Generation (RAG) systems. • Collaborate with data scientists, backend engineers, and product teams to deliver robust AIdriven solutions. • Ensure security, performance, and cost optimization in model training and deployment. • Translate complex business requirements into scalable GenAI solutions. • Maintain best practices in code quality, version control, and documentation. MANDATORY SKILLS: • Proven expertise in LLM fine-tuning, deployment, and inference workflows. • Strong experience in Prompt Engineering and RAG (Retrieval-Augmented Generation) systems. • Proficient in Python with hands-on experience in building AI pipelines. • Demonstrated ability to lead system design and architecture for GenAI applications. PREFERRED SKILLS • Familiarity with GenAI toolkits such as LangChain, LlamaIndex, Haystack, or custom-built frameworks. • Exposure to Microsoft Azure (preferred over AWS or GCP) for cloud deployments. • Experience with scalable, secure AI infrastructure and CI/CD pipelines for ML models Immediate Joiners preferred

Proud to share LSEG in the India is Great Place to Work certified (Jun ’25 – Jun ’26). Learn more about life and purpose of our company directly from India colleagues’ video: Bengaluru, India | Where We Work | LSEG ROLE PROFILE Exciting new opportunity to join LSEG’s Group Investment Management (GIM) – a group level Operations Division that plays a critical role in shaping and overseeing the organisation’s Change Portfolio. The GIM team is responsible for annual Investment Planning and capital allocation across a multi-million (£) Change Portfolio, governed via the Group Investment Committee which the team runs. Beyond investment oversight, the team is responsible for executive reporting on programme delivery performance and development of dashboards and reports to distil large amounts of data into data driven insights and recommendations. Additional responsibilities include carrying out independent delivery assurance and setting the Group-wide delivery framework (standards, guidance and requirements) to ensure best practices are followed and governance requirements are met. Your ability to interpret and utilize data science and analytics to deliver your work and support the team is crucial, in particular with respect to pro-actively measure and predict programme execution risk, using machine learning and AI to develop early warning risk indicators helping steer senior leadership management attention to the parts of the portfolio where delivery of planned benefits and outcomes is at risk of not being met or likely to require substantially more financial commitment than originally asked. The predictive risk metrics you will develop will allow timely management intervention, avoiding costly last minute write off and help foster a delivery discipline and delivery transparency culture. Role Summary Join LSEG’s Group Investment Management team as a Data Scientist, where you’ll play a pivotal role in transforming complex programme data into predictive insights that drive strategic investment decisions. You’ll develop machine learning models and early warning indicators to proactively identify delivery risks across a multi-million-pound change portfolio. This is a unique opportunity to apply your data science expertise in a high-impact, enterprise-level environment that values innovation, transparency, and delivery excellence. Key Accountabilities: Develop and deploy predictive analytics and machine learning models to assess programme execution risk. Translate large, complex datasets into actionable insights and executive-level dashboards. Support investment governance and assurance by providing data-driven recommendations and risk indicators. What It Takes to Be Successful: Strong technical foundation in data science, machine learning, and statistical modelling. Ability to communicate complex findings clearly to non-technical stakeholders. A proactive mindset, with a passion for solving business problems and driving change through data. What You’ll Be Doing Design and implement machine learning models to predict programme delivery risks and financial overruns. Help integrate the insight generated into existing dashboards and visualisations to communicate insights to senior leadership, in collaboration with existing MI teams. Ensure that risk metrics and insights are actionable and trackable. Collaborate with stakeholders across the business to understand data needs and translate them into technical solutions. Conduct data cleaning, preprocessing, and integration from multiple sources (internal databases, APIs). Contribute to the development of the Group-wide delivery framework and assurance standards. Stay current with advancements in AI/ML and apply them to improve risk prediction and decision-making. Support the annual investment planning process with data-driven analysis and scenario modelling. What You’ll Bring Essential Skills: Proficiency in Python or R, with experience in libraries such as scikit-learn, TensorFlow, or similar. Experience in LLM prompt engineering for systematic feature extraction from unstructured data Strong SQL and data wrangling skills; experience with ETL processes. Solid understanding of statistical analysis and hypothesis testing. Experience building and deploying machine learning models in a business context. Ability to communicate technical insights to non-technical audiences through visualisation tools (e.g., Tableau, matplotlib). Desirable Skills: Familiarity with fine tuning small LLM models to automate small topic extraction tasks from unstructured data Familiarity with cloud platforms (e.g., AWS), especially AWS Bedrock and Snowflake data platform. Experience with enterprise programme management tools such as Clarity, Asana, and JIRA. Knowledge of SAP ERP and Workday systems data. Experience in financial services or programme delivery environments. Soft Skills: Analytical thinker with a problem-solving mindset. Strong communication and collaboration skills. Self-starter with the ability to manage multiple priorities in a fast-paced environment. Commitment to continuous learning and innovation. 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.

Salary : 45 to 60LPA Exp: 12 to 20 years Location : Remote Notice: Immediate to 30 days..!! Roles & responsibilities: 10+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 5+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Job Description : You are passionate about cutting-edge technology and keen on applying new AI/ML algorithms and approaches. You are analytically driven, intellectually curious, and experienced leading the development and implementation of data and analytic solutions to solve challenging business problems. You have excellent understanding of web frameworks for quickly showcasing the features and functionalities of the solution. You enjoy collaborating with other data scientists to crack hard to solve problems with AI/ML and seeing it deployed in-market and generating value for Guardian. You enjoy collaborating with a multi-disciplinary team including data engineers, business analysts, software developers and functional business experts and business leaders. You have: • 8+ years of experience in Statistics, Computer Science, Engineering, Applied mathematics or related field • 5+ years of hands-on ML modeling/development experience • Solid understanding of data analysis and statistical modeling. • Solid experience with web frameworks like Streamlit, Flask, Django etc • Knowledge of a variety of machine learning techniques (clustering, decision tree, bagging/boosting artificial neural networks, etc.) and their real-world advantages/drawbacks. • Demonstrated track records in experimental design and executions • Hands-on experience with data wrangling including fuzzy matching and regular expression, distributed computing and applying parallelism to ML solutions • Strong programming skills in Python • Solid background in algorithms and a range of ML models • Excellent communication skills and ability to work and collaborating cross-functionally with Product, Engineering, and other disciplines at both the leadership and hands-on level • Excellent analytical and problem-solving abilities with superb attention to detail • Proven leadership in providing technical leadership and mentoring to data scientists and strong management skills with ability to monitor/track performance for enterprise success Job Description : You are pa ssion ate about cutting-edge technology and keen on apply ing GenAI algori t hms and approaches . Yo u a re analytical ly driven, inte l lectually cur iou s, and experienced leading the development and implementation of data and analytic solutions to solve challenging business problems. You are mostly an Individual Contributor who enjoy s crack ing hard to solve problems with recent LLMs and seeing it deployed in-market and generating value for Guardian. You enjoy collaborating with a multi-disciplinary team including data engineers, business analysts, software developers and functional business experts and business leaders. You have demonstrated track record of managing data science teams and working with business leaders. You have: PhD with 6+ years of experience, Master's degree with 8+ years of expe rienc e, or B achel or's degree with 10+ years of experience in Computer Science, Engineering, A pplied mathem atics or related field 7+ years of hands-on ML modeling/development experience Experience in creating GenAI and Agentic AI applications Solid working knowledge of the engineering components essential in a Gen AI application, including Vector DB, caching layer, chunking, and embedding Knowledge of a variety of machine learning techniques (clustering, decision tree, bagging/boosting artificial neural networks, etc.) and their real-world advantages/drawbacks. Demonstrated track records in experimental design and executions Strong ski lls i n Python , PyTorch , Langchain , LangGraph etc Solid background in algorithms and a range of ML models Excellent communication skills and ability to work and collaborating cross-functionally with Product, Engineering, and other disciplines at both the leadership and hands-on level Excellent analytical and problem-solving abilities wit h superb attention to detail Proven leadership in providing tec hnical le adership and mentoring to data scientists and strong management skills with ability to monitor /track performance for enterprise success Location: This position can be based in any of the following locations: Chennai, Gurgaon For internal use only: R000107556

Key Responsibilities Model Development & Implementation: Design, build, and deploy robust statistical and machine learning models (e.g., for classification, regression, clustering) to predict outcomes and optimise key business metrics. Advanced Analytics: Dive deep into large, complex datasets to identify meaningful patterns, trends, and causal relationships that answer critical business questions. Data Storytelling & Visualisation: Translate complex analytical findings into clear, compelling narratives and visualisations for both technical and non-technical stakeholders using tools like Power BI, Tableau, or SAS Visual Analytics. Data Preparation & Engineering: Take ownership of the data lifecycle, including cleaning, pre-processing, and transforming raw data into high-quality, analysis-ready datasets. Experimental Design: Design and execute A/B tests and other experiments to validate hypotheses and measure the impact of new strategies. Cross-Functional Collaboration: Partner closely with business analysts, data engineers, and product managers to define project requirements, develop solutions, and integrate them into our operational workflows. Continuous Innovation: Stay current with the latest advancements in data science, machine learning, and AI, and champion the adoption of new technologies and methodologies within the team. Skills & Qualifications We believe the right candidate will have a blend of technical expertise, business acumen, and strong interpersonal skills. Required: Education: An Honours degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Engineering, or Econometrics. Core Programming: High proficiency in Python (including libraries like pandas, NumPy, scikit-learn) and/or SAS, paired with strong SQL skills for data extraction and manipulation. Statistical Foundation: A deep understanding of statistical concepts, experimental design, and modelling techniques. Machine Learning: Hands-on experience developing and deploying machine learning models using libraries such as scikit-learn, TensorFlow, or PyTorch. Communication: Exceptional ability to articulate complex technical concepts and findings clearly and concisely to diverse audiences. Problem-Solving: Strong critical-thinking and analytical skills with a proven ability to solve ambiguous problems with data. Preferred: Education: A Master’s degree or PhD in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Engineering, or Econometrics. Data Visualisation: Demonstrable experience creating insightful dashboards and reports in tools like Power BI, Tableau, or SAS Visual Analytics. Big Data Technologies: Familiarity with distributed computing frameworks like Apache Spark or Hadoop. Cloud Platforms: Experience working with data services on cloud platforms such as AWS, Azure, or GCP.

• Total experience 5+ years • Working experience in Python • Experience with data visualization • working experience of DS stack packages • Experience working with GCP/AWS cloud services • Hands-on experience deploying ML solutions

Job Responsibilities of this position : 1. Lead and architect the design and development of AI/ML predictive models that significantly enhance decision-making processes for clients, leveraging their own historical data sets and industry insights. 2. Engage with senior executives and key stakeholders to fully understand their business needs, strategic objectives, and data requirements, ensuring the AI/ML models are precisely tailored to deliver maximum business value. 3. Oversee the implementation, testing, and validation of machine learning algorithms, ensuring that the models are not only accurate but also scalable, reliable, and robust for enterprise-level production environments. 4. Collaborate cross-functionally with product managers, engineers, and data scientists to integrate AI/ML models into Xemplar’s product ecosystem, optimizing performance and efficiency across multiple teams. 5. Provide expert analysis and interpretation of complex data sets from various sources, delivering actionable insights that inform business decisions and improve the accuracy and predictive power of models. 6. Stay ahead of emerging AI/ML trends and innovations, actively incorporating cutting-edge research, techniques, and best practices into the modeling and development processes. 7. Drive the technical vision and strategic direction for AI/ML initiatives, mentoring and guiding less experienced team members while also establishing best practices and a culture of continuous improvement. 8. Partner with business analysts, frontend, mid-tier, and backend developers to ensure the development, deployment, and performance of production applications that effectively utilize AI/ML models to deliver real-world impact. 9. Take ownership of solving complex, ambiguous problems with minimal supervision, applying advanced theoretical knowledge to conceptualize, simulate, and implement AI/ML solutions. 10. Define and manage data requirements and data quality assessments, orchestrating the extraction, transformation, and integration of data for analytical and modeling projects. Required Relevant Experience: ✓ 10+ years of experience in developing and deploying AI/ML predictive models in production environments, with a strong portfolio of successful enterprise-scale projects and solutions. ✓ Expertise in machine learning techniques, including but not limited to regression, classification, clustering, time series analysis, and deep learning. ✓ Advanced proficiency in programming languages such as Python, R, or similar, and mastery of machine learning libraries (e.g., TensorFlow, scikit-learn, PyTorch). ✓ Extensive experience with data wrangling, feature engineering, and working with large, complex, high-volume datasets. ✓ Proven track record in model validation and testing, ensuring models are robust, reliable, and scalable across different use cases and environments. ✓ Deep understanding of the P&C Insurance domain, with specific experience in areas like claims prediction, risk modeling, pricing optimization, and customer segmentation. ✓ Strong ability to communicate complex technical concepts to senior, non-technical stakeholders, influencing decision-making at the highest levels. ✓ Significant hands-on experience working with both structured and unstructured data at scale, with expertise in cloud platforms, distributed computing, and big data technologies. ✓ 10+ years of experience in predictive model development, data mining, statistical modeling, and high-performance computing in complex enterprise environments.

Bhubaneswar, India Job Category : Data Scientist Posting Date : 01 January 2024 Job Type : Engineering Years of Experience : 5 Does this position require a security clearance? No Applicants are required to read,write and speak the following languages Hindi/English Additional Info : Job Description Are you seeking your next career advancement? At our company, we present thrilling prospects for skilled professionals in a diverse range of job fields and positions. Come on board with us to create remarkable achievements. We take pride in being the fastest-growing enterprise resource planning platform, attracting new customers to our advanced system for expediting their business processes. Our teams diligently contribute towards our triumph, each with a crucial role to fulfill. Responsibilities Develop and create AI/ML based predictive solutions and enhance or upgrade existing ones. Collaborate and communicate effectively with various teams within Nirmalya. Establish strong partnerships with business representatives to fully grasp their requirements. Engage proficiently with other teams and individuals. Proficient in programming languages like Python. Exceptional verbal and written English communication abilities. Outstanding troubleshooting and problem-solving skills. Possess a curious mindset to tackle exciting new subjects. Display a high level of curiosity, motivation, and eagerness to learn new technologies. Valuable team player with fast learning abilities. Encouraged to contribute own ideas and perspectives openly. Qualifications Bachelor's or higher degree in computer science or a related technical/scientific discipline. Strong analytical skills required, including a thorough understanding of how to interpret customer business needs and translate them into solutions and operational requirements. Excellent verbal and written communication skills and the ability to interact professionally with a diverse group, executives, managers, and subject matter experts. Required Skills Proficiency in mathematics, statistics, computer science, or related fields is required. Preferably, expertise in linear algebra, calculus, and statistics. In-depth knowledge of data science and predictive methodologies is essential. Familiarity with agile working methodologies such as SAFe, SCRUM, KANBAN, etc. is advantageous. Capable of managing multiple projects simultaneously. Additional programming skills are highly advantageous (optional). Disclaimer Hiring Range: from 1000000 to 2250000 per annum. May be eligible for bonus and equity. We maintain broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Nirmalya’s differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. About Us Nirmalya's career has the potential to encompass various industries, roles, countries, and cultures, allowing for growth in novel positions and driving innovation, while effectively balancing work and personal life. Nirmalya has achieved success over the years by embracing change, fostering innovation, and consistently upholding ethical principles, thereby delivering exceptional results for leading companies across multiple industries.To foster and support the talents responsible for such accomplishments, our dedication lies in cultivating an inclusive culture that appreciates and embraces diverse insights and perspectives. We strive to create a workforce that inspires thought leadership and sparks innovation, ensuring a thriving environment for all. Nirmalya Employee Benefits are meticulously designed to prioritize equality, reliability, and affordability. Our comprehensive package encompasses essential features such as Medical and Life Insurance, while also granting access to Retirement Planning and more. Additionally, we actively encourage our employees to actively contribute to the well-being of the communities where we operate. We firmly believe that fostering diversity and inclusion lays the foundation for innovation. To shape a brighter tomorrow, we seek talent from diverse backgrounds, embracing a range of perspectives and abilities. We are committed to providing reasonable accommodations to individuals with disabilities throughout the job application, interview, and prospective role stages, thereby enabling them to effectively perform crucial job functions. Our dedication lies in fostering an inclusive workforce that enables every individual to thrive. We believe in the power of diverse perspectives and value every voice, as it is this harmony that propels us to surpass previous achievements. As an Equal Employment Opportunity Employer, Nirmalya ensures that all applicants are treated fairly and without discrimination. We promote equality regardless of race, color, religion, national origin, gender identity, disability, protected veterans’ status, or any other characteristic protected by law. Additionally, Oracle complies with applicable legislation by considering qualified applicants with arrest and conviction records for employment opportunities. Join our team where diversity is celebrated, and everyone's unique contribution is respected. Together, we embrace innovation and strive towards excellence – a testament to our commitment to fostering an inclusive and thriving workplace.

Should have exp with Agen c frameworks like Crew AI, Lang, graph, Swarm AI etc. Must have contributed significantly to the development of at least 2 Gen AI projects. Must have worked with mul ple Gen AI models including GPT, Claude, Qwen, Lama etc.