657 Xgboost Jobs - Page 18

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. The Defender Experts (DEX) Research team is at the forefront of Microsoft’s threat protection strategy, combining world-class hunting expertise with AI-driven analytics to protect customers from advanced cyberattacks. Our mission is to move protection left—disrupting threats early, before damage occurs—by transforming raw signals into intelligence that powers detection, disruption, and customer trust. We’re looking for a passionate and curious Data Scientist to join this high-impact team. In this role, you'll partner with researchers, hunters, and detection engineers to explore attacker behavior, operationalize entity graphs, and develop statistical and ML-driven models that enhance DEX’s detection efficacy. Your work will directly feed into real-time protections used by thousands of enterprises and shape the future of Microsoft Security. This is an opportunity to work on problems that matter—with cutting-edge data, a highly collaborative team, and the scale of Microsoft behind you. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Design and build robust, large-scale graph structures to model security entities, behaviors, and relationships. Develop and deploy scalable, production-grade AI/ML systems and intelligent agents for real-time threat detection, classification, and response. Collaborate closely with Security Research teams to integrate domain knowledge into data science workflows and enrich model development. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Work with large-scale graph data: create, query, and process it efficiently to extract insights and power models. Lead initiatives involving Graph ML, Generative AI, and agent-based systems, driving innovation across threat detection, risk propagation, and incident response. Collaborate closely with engineering and product teams to integrate solutions into production platforms. Mentor junior team members and contribute to strategic decisions around model architecture, evaluation, and deployment. Qualifications Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field 6+ years of experience applying data science or machine learning in a real-world setting, preferably in security, fraud, risk, or anomaly detection Proficiency in Python and/or R, with hands-on experience in data manipulation (e.g., Pandas, NumPy), modeling (e.g., scikit-learn, XGBoost), and visualization (e.g., matplotlib, seaborn) Strong foundation in statistics, probability, and applied machine learning techniques Experience working with large-scale datasets, telemetry, or graph-structured data Ability to clearly communicate technical insights and influence cross-disciplinary teams Demonstrated ability to work independently, take ownership of problems, and drive solutions end-to-end Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations. Show more Show less

Key Responsibilities Design, develop, and deploy machine learning models for prediction, recommendation, anomaly detection, NLP, or image processing tasks. Work with large, complex datasets to extract insights and build scalable solutions. Collaborate with data engineers to create efficient data pipelines and feature engineering workflows. Evaluate model performance using appropriate metrics and improve models through iterative testing and tuning. Communicate findings, insights, and model outputs clearly to non-technical stakeholders. Stay up to date with the latest machine learning research, frameworks, and technologies. Required Skills Strong programming skills in Python (Pandas, NumPy, Scikit-learn, etc.). Hands-on experience with ML/DL frameworks like TensorFlow, PyTorch, XGBoost, or LightGBM. Experience in building, deploying, and maintaining end-to-end ML models in production. Solid understanding of statistics, probability, and mathematical modeling. Proficiency with SQL and data manipulation in large-scale databases. Familiarity with version control (Git), CI/CD workflows, and model tracking tools (MLflow, DVC, etc.). Preferred Skills Experience with cloud platforms like AWS, GCP, or Azure (e.g., SageMaker, Vertex AI). Knowledge of MLOps practices and tools for scalable ML deployments. Exposure to real-time data processing or streaming (Kafka, Spark). Experience with NLP, Computer Vision, or Time Series Forecasting. Show more Show less

The Purpose of the role We are seeking a full stack data scientist in Advanced Analytics team, who will be at the forefront of developing new innovative data driven solutions with bleeding edge machine learning and AI solution end to end. AIML Data Scientist is a technical job that uses AI & machine learning techniques to automate underwriting processes, improve claims outcomes and/or risk solutions. This person will develop vibrant data science solutions which require data engineering, AlML algorithms and Ops engineering skills to develop and deploy it for the business. Ideal candidate for this role is someone with a strong education in computer science, data science, statistics, applied math or a related field, and who is eager to tackle problems with innovative thinking without compromising detail business insights. You are adept at solving diverse problems by utilizing a variety of different tools, strategies, machine learning techniques, algorithms and programming languages. Responsibilities Work with business partners globally, determine analyses to be performed, manage deliverables against timelines, present of results and implement the model. Use broad spectrum of Machine Learning, text and image AI models to extract impactful features from structured/unstructured data. Develop and implement models that help with automating, getting insights, make smart decisions; Ensure that the model is able to meet the desired KPIs post-production. Develop and deploy scalable and efficient machine learning models. Package and publish codes and solutions in reusable format python package format- (Pypi, Scikit-learn pipeline,..) Keep the code ready for seamless building of CI/CD pipelines and workflows for machine learning applications. Ensure high quality code that meets business objectives, quality standards and secure web development guidelines. Building reusable tools to streamline the modeling pipeline and sharing knowledge Build real-time monitoring and alerting systems for machine learning systems. Develop and maintain automated testing and validation infrastructure. Troubleshoot pipelines across multiple touchpoints like CI Server, Artifact storage and Deployment cluster. Implement best practices for versioning, monitoring and reusability. Requirements Sound understanding of ML concepts, Supervised / Unsupervised Learning, Ensemble Techniques, Hyperparameter Good knowledge of Random Forest, XGBoost, SVM, Clustering, building data pipelines in Azure/Databricks, deep learning models, OpenCV, Bert and new transformer models for NLU, LLM application in ML> Strong experience with Azure cloud computing and containerization technologies (like Docker, Kubernetes). 4-6 years of experience in delivery end to end data science models. Experience with Python/OOPs programming languages and data science frameworks like (Pandas, Numpy, TensorFlow, Keras, PyTorch, sklearn). Knowledge of DevOps tools such as Git, Jenkins, Sonar, Nexus is must. Building python wheels and debugging build process. Data pipeline building and debugging (by creating and following log traces). Basic knowledge of DevOps practices. Concepts of Unit Testing and Test-Driven development. SDE skills like OOP and Functional programming are an added advantage. Experience with Databricks and its ecosystem is an added advantage. analytics/statistics/mathematics or related domain. Show more Show less

Responsibilities Build and fine-tune models for NLP, computer vision, predictions, and more. Engineer intelligent pipelines that are used in production. Collaborate across teams to bring AI solutions to life (not just in Jupyter Notebooks). Embrace MLOps with tools like MLflow, Docker, and Kubernetes. Stay on the AI cutting edge and share what you learnmentorship mindset is a big plus. Champion code quality and contribute to a future-focused dev culture. Requirements 3-4 years in hardcore AI/ML or applied data science. Pro-level Python skills (R is cool too, but Python is king here). Mastery over ML frameworks: scikit-learn, XGBoost, LightGBM, TensorFlow/Keras, PyTorch. Hands-on with real-world data wrangling, feature engineering, and model deployment. DevOps-savvy: Docker, REST APIs, Git, and maybe even some MLOps sparkle. Cloud comfort: AWS, GCP, or Azure - take your pick. Solid grasp of Agile, good debugging instincts, and a hunger for optimization. This job was posted by Sampurna Pal from AmpleLogic. Show more Show less

Job Summary: We are looking for a highly skilled Data Scientist with deep expertise in time series forecasting, particularly in demand forecasting and customer lifecycle analytics (CLV). The ideal candidate will be proficient in Python or PySpark, have hands-on experience with tools like Prophet and ARIMA, and be comfortable working in Databricks environments. Familiarity with classic ML models and optimization techniques is a plus. Key Responsibilities • Develop, deploy, and maintain time series forecasting models (Prophet, ARIMA, etc.) for demand forecasting and customer behavior modeling. • Design and implement Customer Lifetime Value (CLV) models to drive customer retention and engagement strategies. • Process and analyze large datasets using PySpark or Python (Pandas). • Partner with cross-functional teams to identify business needs and translate them into data science solutions. • Leverage classic ML techniques (classification, regression) and boosting algorithms (e.g., XGBoost, LightGBM) to support broader analytics use cases. • Use Databricks for collaborative development, data pipelines, and model orchestration. • Apply optimization techniques where relevant to improve forecast accuracy and business decision-making. • Present actionable insights and communicate model results effectively to technical and non-technical stakeholders. Required Qualifications • Strong experience in Time Series Forecasting, with hands-on knowledge of Prophet, ARIMA, or equivalent – Mandatory. • Proven track record in Demand Forecasting – Highly Preferred. • Experience in modeling Customer Lifecycle Value (CLV) or similar customer analytics use cases – Highly Preferred. • Proficiency in Python (Pandas) or PySpark – Mandatory. • Experience with Databricks – Mandatory. • Solid foundation in statistics, predictive modeling, and machine learning. Show more Show less

Senior Applied & Data scientist Hyderabad, Telangana, India Date posted Jun 16, 2025 Job number 1830452 Work site Up to 50% work from home Travel 0-25 % Role type Individual Contributor Profession Research, Applied, & Data Sciences Discipline Data Science Employment type Full-Time Overview Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. The Defender Experts (DEX) Research team is at the forefront of Microsoft’s threat protection strategy, combining world-class hunting expertise with AI-driven analytics to protect customers from advanced cyberattacks. Our mission is to move protection left—disrupting threats early, before damage occurs—by transforming raw signals into intelligence that powers detection, disruption, and customer trust. We’re looking for a passionate and curious Data Scientist to join this high-impact team. In this role, you'll partner with researchers, hunters, and detection engineers to explore attacker behavior, operationalize entity graphs, and develop statistical and ML-driven models that enhance DEX’s detection efficacy. Your work will directly feed into real-time protections used by thousands of enterprises and shape the future of Microsoft Security. This is an opportunity to work on problems that matter—with cutting-edge data, a highly collaborative team, and the scale of Microsoft behind you. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Qualifications Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field 6+ years of experience applying data science or machine learning in a real-world setting, preferably in security, fraud, risk, or anomaly detection Proficiency in Python and/or R, with hands-on experience in data manipulation (e.g., Pandas, NumPy), modeling (e.g., scikit-learn, XGBoost), and visualization (e.g., matplotlib, seaborn) Strong foundation in statistics, probability, and applied machine learning techniques Experience working with large-scale datasets, telemetry, or graph-structured data Ability to clearly communicate technical insights and influence cross-disciplinary teams Demonstrated ability to work independently, take ownership of problems, and drive solutions end-to-end Responsibilities Design and develop data-driven models and algorithms to identify emerging attacker behavior, anomalies, and threat patterns at scale Build and operationalize statistical/ML systems that power early-stage detection, disruption scoring, and alert prioritization within DEX workflows Analyze high-dimensional security telemetry (e.g., token usage, entity relationships, campaign data) to derive signal enrichment and protection insights Collaborate closely with security researchers, threat hunters, and engineers to translate hypotheses into deployable detection logic Lead data investigations on false positives, missed threats, or campaign-level attack patterns to inform detection strategy and service improvement Contribute to the design of entity-based graph pipelines and verdict propagation mechanisms for pre-breach signal interpretation Drive experimentation and model explainability to ensure robustness, interpretability, and operational relevance of developed systems Communicate technical findings to cross-functional stakeholders and influence product and detection roadmap decisions Author internal whitepapers, prototypes, or publications to push the boundaries of applied data science in security Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.  Industry leading healthcare  Educational resources  Discounts on products and services  Savings and investments  Maternity and paternity leave  Generous time away  Giving programs  Opportunities to network and connect Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

JOB DESCRIPTION About KPMG in India KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada. KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment. TempHtmlFile About KPMG in India KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada. KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment. About: Our Financial Crimes specialist teams provide solutions to BFSI clients by conducting model validation testing for AML risk models and frameworks, sanctions screening and transaction monitoring system to ensure efficiency and efficacy of underlying frameworks both functionally and statistically. We are looking to hire colleagues with advance data science and analytics skill to support our financial crimes team. You will play a crucial role in helping clients tackle the multifaceted challenges of financial crime. By utilizing advanced analytics and deep technical knowledge, our team aids top clients in reducing risks associated with financial crime, terrorist financing, and sanctions violations. We also work to enhance their screening and transaction monitoring systems. Our team of specialized analysts ensures that leading financial institutions adhere to industry best practices for robust programs and controls. Through a variety of project experiences, you will develop your professional skills, assisting clients in understanding and addressing complex issues, and implementing top-tier solutions to resolve identified problems. Minimum work experience: 3+ years of advance analytics Preferred experience: 1+ years in AML model validation Responsibilities · Support functional SME teams to build data driven Financial Crimes solution · Conduct statistical testing of the screening matching algorithms, risk rating models and thresholds configured for detection rules · Validate data models of AML systems built on systems such as SAS Viya, Actimize, Lexis Nexis, Napier, etc. · Develop, validate, and maintain AML models to detect suspicious activities and transactions. · Conduct Above the Line and Below the Line testing · Conduct thorough model validation processes, including performance monitoring, tuning, and calibration. · Ensure compliance with regulatory requirements and internal policies related to AML model risk management. · Collaborate with cross-functional teams to gather and analyze data for model development and validation. · P erform data analysis and statistical modeling to identify trends and patterns in financial transactions. · Prepare detailed documentation and reports on model validation findings and recommendations. · Assist in feature engineering for improvising Gen AI prompts applicable for automation of AML / Screening related investigations · Use advanced Machine Learning deployment (e.g. XGBoost) and GenAI approaches Criteria: · Bachelor’s degree from accredited university · 3+ years of complete hands-on experience in Python with an experience in Java, Fast, Django, Tornado or Flask frameworks · Working experience in Relational and NoSQL databases like Oracle, MS SQL MongoDB or ElasticSearch · Proficiency BI tools such as Power BI, Tableau, etc. · Proven experience in data model development and testing · Education background in Data Science and Statistics · Strong proficiency in programming languages such as Python, R, and SQL. · Expertise in machine learning algorithms, statistical analysis, and data visualization tools. · Familiarity with regulatory guidelines and standards for AML · Experience in AML related model validation and testing · Expertise in techniques and algorithms to include sampling, optimization, logistic regression, cluster analysis, Neural Networks, Decision Trees, supervised and unsupervised machine learning Preferred experiences: Validation of AML compliance models such as statistical testing of customer / transaction risk models, screening algorithm testing, etc. Experience with developing proposals (especially new solutions) Experience working AML technology platforms e.g. Norkom, SAS, Lexis Nexis, etc. Hands on experience with data analytics tools using Informatica, Kafka, etc. Equal employment opportunity information KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you. QUALIFICATIONS Bachelor’s degree from accredited university · Education background in Data Science and Statistics · 3+ years of complete hands-on experience in data science and data analytics

We are seeking a data scientist with strong technical expertise in machine learning and statistical analysis to develop and deploy impactful data solutions. The role involves designing and implementing predictive models (e.g., regression, classification, NLP, time series), collaborating with stakeholders to solve business problems, and driving strategic decisions through experimentation and data-driven insights Job Description: Key responsibilities: 1. Modeling & Machine Learning Design and implement robust machine learning solutions (e.g., regression, classification, NLP, time series, recommendation systems). Evaluate and tune models using appropriate metrics (AUC, RMSE, precision/recall, etc.). Work on feature engineering, model interpretability, and performance optimization. 2. Data-Driven Business Strategy Partner with stakeholders to identify key opportunities where data science can drive business value. Translate business problems into data science projects with clearly defined deliverables and success metrics. Provide actionable recommendations based on data analysis and model outputs. 3. Analytics and Experimentation Conduct deep-dive exploratory analysis to uncover trends and insights. Apply statistical methods to test hypotheses, forecast trends, and measure campaign effectiveness Design and analyze A/B tests and other experiments to support product and marketing decisions. Automate data pipelines and dashboards for ongoing monitoring of model and business performance. Technical Skills: Languages: Proficient in Python, MySQL. Libraries/Frameworks: scikit-learn, Pandas, NumPy, Time series, ARIMA, Bayesian model, Market Mix model, Regression, XGBoost, LightGBM, TensorFlow, PyTorch. Statistical Method: Proficient in statistical techniques such as hypothesis testing, regression analysis, time-series analysis Databases : PostgreSQL, BigQuery, MySQL. Visualization: Plotly, Seaborn, Matplotlib. Deployment: Experience in Gitlab, CI/CD pipelines(Good to have). Cloud Platforms: Familiarity with AWS, GCP, or Azure services(Good to have). Location: Chennai Brand: Paragon Time Type: Full time Contract Type: Permanent

Red & White Education Pvt Ltd , founded in 2008, is Gujarat's leading educational institute. Accredited by NSDC and ISO, we focus on Integrity, Student-Centricity, Innovation, and Unity. Our goal is to equip students with industry-relevant skills and ensure they are employable globally. Join us for a successful career path. Job Description: Faculties guide students, deliver course materials, conduct lectures, assess performance, and provide mentorship. Strong communication skills and a commitment to supporting students are essential. Key Responsibilities: Deliver high-quality lectures on AI, Machine Learning, and Data Science . Design and update course materials, assignments, and projects. Guide students on hands-on projects, real-world applications, and research work. Provide mentorship and support for student learning and career development. Stay updated with the latest trends and advancements in AI/ML and Data Science. Conduct assessments, evaluate student progress, and provide feedback. Participate in curriculum development and improvements. Skills & Tools: Core Skills: ML, Deep Learning, NLP, Computer Vision, Business Intelligence, AI Model Development, Business Analysis. Programming: Python, SQL (Must), Pandas, NumPy, Excel. ML & AI Tools: Scikit-learn (Must), XGBoost, LightGBM, TensorFlow, PyTorch (Must), Keras, Hugging Face. Data Visualization: Tableau, Power BI (Must), Matplotlib, Seaborn, Plotly. NLP & CV: Transformers, BERT, GPT, OpenCV, YOLO, Detectron2. Advanced AI: Transfer Learning, Generative AI, Business Case Studies. Education & Experience Requirements: Bachelor's/Master’s/Ph.D. in Computer Science, AI, Data Science, or a related field. Minimum 1+ years of teaching or industry experience in AI/ML and Data Science. Hands-on experience with Python, SQL, TensorFlow, PyTorch, and other AI/ML tools. Practical exposure to real-world AI applications, model deployment, and business analytics. Additional Skills: Confident body language and clear communication. Strong classroom management and discipline skills. Punctual, prepared, and passionate about teaching. Open to learning and professional development. Proficient in verbal and written communication. Strong problem-solving, leadership, and decision-making abilities. Positive attitude and ability to work independently. For further information, please feel free to contact 7862813693 us via email at career@rnwmultimedia.edu.in Job Types: Full-time, Permanent Pay: ₹30,000.00 - ₹35,000.00 per month Benefits: Cell phone reimbursement Flexible schedule Leave encashment Paid sick time Paid time off Schedule: Day shift Morning shift Supplemental Pay: Performance bonus Yearly bonus Application Question(s): Current Salary? Experience: Teaching / Mentoring: 1 year (Required) AI: 1 year (Required) ML: 1 year (Required) Data science: 1 year (Required) Location: Ahmedabad, Gujarat (Required) Work Location: In person

Introduction At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk. Your Role And Responsibilities In the IBM Chief Information Office, you will be part of a dynamic team driving the future of AI and data science in large-scale enterprise transformations. We offer a collaborative environment where your technical expertise will be valued, and your professional development will be supported. Join us to work on challenging projects, leverage the latest technologies, and make a tangible impact on leading organisations. As a Data Scientist within IBM's Chief Information Office, you will support AI-driven projects across the enterprise. You will apply your technical skills in AI, machine learning, and data analytics to assist in implementing data-driven solutions that align with business goals. This role involves working with team members to translate data insights into actionable recommendations. Key Responsibilities Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimisation of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyse complex datasets and generate actionable insights. Learn and utilise cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. Collaboration: Ensure alignment to stakeholders’ strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams. Preferred Education Master's Degree Required Technical And Professional Expertise Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree is strongly preferred Experience 5+ years of experience in data science, AI, or analytics with a focus on implementing data-driven solutions Experience with data cleaning, data analysis, A/B testing, and data visualization Experience with AI technologies through coursework or projects Technical Skills Proficiency in SQL and Python for performing data analysis and developing machine learning models Knowledge of common machine learning algorithms and frameworks: linear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience with cloud-based platforms and data processing frameworks Understanding of large language models (LLMs) Familiarity with IBM’s watsonx product suite Familiarity with object-oriented programming Analytical Skills Strong problem-solving abilities and eagerness to learn Ability to work with datasets and derive insights Other Requirements Good communication skills, with the ability to explain technical concepts clearly Enthusiasm for learning and applying new technologies Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment. Successful completion of Coding Assessment Preferred Technical And Professional Experience Data Science specialized Show more Show less

Job Responsibilities: We are seeking an experienced Data Scientist to lead the development of a Data Science program . You will work closely with various stakeholders to derive deep industry knowledge across paper, water, leather, and performance chemical industries . You will help develop a data strategy for the company including collection of the right data, creation of the data science project portfolio, partnering with external providers , and augmenting capabilities with additional internal hires. A large part of the job is communicating and developing relationships with key stakeholders and subject matter experts to tee up proofs of concept (PoC) projects to demonstrate how data science can solve old problems in unique and novel ways . You will not have a large internal team to rely on, at least initially, so individual expertise, breadth of data science knowledge , and ability to partner with external companies will be essential for success. In addition to the pure data science problems, you will be working closely with a multi-disciplinary team consisting of sensor scientists, software engineers, network engineers, mechanical/electrical engineers, and chemical engineers in the development and deployment of IoT solutions . Basic Qualification: Bachelor’s degree in a quantitative field such as Data Science, Statistics, Applied Mathematics, Physics, Engineering, or Computer Science 5+ years of relevant working experience in an analytical role involving data extraction, analysis, and visualization and expertise in the following areas: Expertise in one or more programming languages : R, Python, MATLAB, JMP, Minitab, Java, C++, Scala Key libraries such as Sklearn, XGBoost, GLMNet, Dplyr, ggplot, RShiny Experience and knowledge of data mining algorithms including supervised and unsupervised machine learning techniques in areas such as Gradient Boosting, Decision Trees, Multivariate Regressions, Logistic Regression, Neural Network, Random Forest, SVM, Naive Bayes, Time Series, Optimization Microsoft IoT/data science toolkit : Azure Machine Learning, Datalake, Datalake Analytics, Workbench, IoT Hub, Stream Analytics, CosmosDB, Time Series Insights, Power BI Data querying languages : SQL, Hadoop/Hive A demonstrated record of success with a verifiable portfolio of problems tackled Preferred Qualifications: Master’s or PhD degree in a quantitative field such as Data Science, Statistics, Applied Mathematics, Physics, Engineering, or Computer Science Experience in the specialty chemicals sector or similar industry Background in engineering, especially Chemical Engineering Experience starting up a data science program Experience working with global stakeholders Experience working in a start-up environment, preferably in an IoT company Knowledge in quantitative modeling tools and statistical analysis Personality Traits: A strong business focus, ownership, and inner self-drive to develop data science solutions to real-world customers with tangible impact. Ability to collaborate effectively with multi-disciplinary and passionate team members . Ability to communicate with a diverse set of stakeholders . Strong planning and organization skills , with the ability to manage multiple complex projects . A life-long learner who constantly updates skills. Show more Show less

We are looking for a highly skilled and motivated Data Scientist with deep experience in building recommendation systems to join our team. This role demands expertise in deep learning, embedding-based retrieval, and the Google Cloud Platform (GCP). You will play a critical role in developing intelligent systems that enhance user experiences through personalized content discovery. Key Responsibilities: Develop, train, and deploy recommendation models using two-tower, multi-tower, and cross-encoder architectures . Generate and utilize text/image embeddings (e.g., CLIP , BERT , Sentence Transformers ) for content-based recommendations. Design semantic similarity search pipelines using vector databases (FAISS, ScaNN, Qdrant, Matching Engine). Create and manage scalable ML pipelines using Vertex AI , Kubeflow Pipelines , and GKE . Handle large-scale data preparation and feature engineering using Dataproc (PySpark) and Dataflow . Implement cold-start strategies leveraging metadata and multimodal embeddings. Work on user modeling , temporal personalization , and re-ranking strategies . Run A/B tests and interpret results to measure real-world impact. Collaborate with cross-functional teams (Engineering, Product, DevOps) for model deployment and monitoring. Must-Have Skills: Strong command of Python and ML libraries: pandas, polars, numpy, scikit-learn, matplotlib, tensorflow, torch, transformers. Deep understanding of modern recommender systems and embedding-based retrieval . Experience with TensorFlow , Keras , or PyTorch for building deep learning models. Hands-on with semantic search , ANN search , and real-time vector matching . Proven experience with Vertex AI , Kubeflow on GKE , and ML pipeline orchestration. Familiarity with vector DBs such as Qdrant , FAISS , ScaNN , or Matching Engine on GCP. Experience in deploying models via Vertex AI Online Prediction , TF Serving , or Cloud Run . Knowledge of feature stores , embedding versioning , and MLOps practices (CI/CD, monitoring). Preferred / Good to Have: Experience with ranking models (e.g., XGBoost , LightGBM , DLRM ) for candidate scoring. Exposure to LLM-powered personalization or hybrid retrieval systems. Familiarity with streaming pipelines using Pub/Sub , Dataflow , Cloud Functions . Hands-on with multi-modal retrieval (text + image + tabular data). Strong grasp of cold-start problem solving , using enriched metadata and embeddings. GCP Stack You’ll Work With: ML & Pipelines: Vertex AI, Vertex Pipelines, Kubeflow on GKE Embedding & Retrieval: Matching Engine, Qdrant, FAISS, ScaNN, Milvus Processing: Dataproc (PySpark), Dataflow Ingestion & Serving: Pub/Sub, Cloud Functions, Cloud Run, TF Serving CI/CD & Automation: GitHub Actions, GitLab CI, Terraform Show more Show less

We are seeking a data scientist with strong technical expertise in machine learning and statistical analysis to develop and deploy impactful data solutions. The role involves designing and implementing predictive models (e.g., regression, classification, NLP, time series), collaborating with stakeholders to solve business problems, and driving strategic decisions through experimentation and data-driven insights Job Description: Key responsibilities: Modeling & Machine Learning Design and implement robust machine learning solutions (e.g., regression, classification, NLP, time series, recommendation systems). Evaluate and tune models using appropriate metrics (AUC, RMSE, precision/recall, etc.). Work on feature engineering, model interpretability, and performance optimization. Data-Driven Business Strategy Partner with stakeholders to identify key opportunities where data science can drive business value. Translate business problems into data science projects with clearly defined deliverables and success metrics. Provide actionable recommendations based on data analysis and model outputs. Analytics and Experimentation Conduct deep-dive exploratory analysis to uncover trends and insights. Apply statistical methods to test hypotheses, forecast trends, and measure campaign effectiveness Design and analyze A/B tests and other experiments to support product and marketing decisions. Automate data pipelines and dashboards for ongoing monitoring of model and business performance. Technical Skills: Languages: Proficient in Python, MySQL. Libraries/Frameworks: scikit-learn, Pandas, NumPy, Time series, ARIMA, Bayesian model, Market Mix model, Regression, XGBoost, LightGBM, TensorFlow, PyTorch. Statistical Method: Proficient in statistical techniques such as hypothesis testing, regression analysis, time-series analysis Databases : PostgreSQL, BigQuery, MySQL. Visualization: Plotly, Seaborn, Matplotlib. Deployment: Experience in Gitlab, CI/CD pipelines(Good to have). Cloud Platforms: Familiarity with AWS, GCP, or Azure services(Good to have). Location: Chennai Brand: Paragon Time Type: Full time Contract Type: Permanent Show more Show less

About Pocket Entertainment Pocket Entertainment is revolutionizing entertainment through immersive storytelling. With millions of users worldwide, we're building the future of entertainment — blending human creativity with cutting-edge AI. Now, we’re expanding our global footprint. Let’s reimagine global entertainment — powered by AI and fueled by imagination. Work on category-defining AI products reshaping entertainment that operate at massive scale: millions of users, billions of minutes consumed. Collaborate with some of the best engineers, AI researchers, and creators globally. Mission of the role As a Senior Principal Data Scientist at Pocket FM, you will play a pivotal role in driving innovation in recommendation systems , user personalization , and content strategy . You will lead high-impact initiatives to understand user behavior, predict preferences, and enhance engagement through intelligent content delivery. This is a hands-on leadership role where you will set the technical vision, guide the roadmap, influence strategy, and mentor a high-performing data science team. Key responsibilities: Design and deploy machine learning models for recommendations, personalization, ranking, and user behavior prediction Tackle high-impact challenges across personalization, churn prediction, LTV modeling, creator analytics, and platform growth Partner with engineering, product, and content teams to align modeling efforts with business impact Lead the full ML lifecycle: prototyping, experimentation, A/B testing, deployment, and monitoring Translate large-scale user behavior data into actionable insights and strategies for content discovery and retention Mentor and guide junior and senior data scientists, fostering a culture of technical excellence, innovation, and continuous learning Conduct in-depth data analysis and exploratory research to uncover actionable insights, understand user trends, and identify new opportunities for product improvement and growth Drive MLOps best practices including model monitoring, versioning, and lifecycle management Stay current with advances in ML/NLP and apply them to improve recommendation quality and user satisfaction Qualifications: Advanced degree (PhD or Master’s) in CS, ML, Stats, or related field 12+ years of experience building and deploying ML models in production Expertise in recommender systems, personalization, ranking, or user modeling Strong Python skills and deep experience with ML frameworks (e.g., PyTorch, TensorFlow, XGBoost) Solid grounding in experimentation, A/B testing, and statistical inference Experience with big data tools (Spark, Databricks) and cloud platforms (AWS/GCP) Strong analytical and creative problem-solving skills Strong communication and cross-functional collaboration skills Bonus Points: Experience with NLP techniques applied to text or audio data Contributions to open-source ML projects or research publications Familiarity with generative AI models and their applications Show more Show less

Red & White Education Pvt Ltd , founded in 2008, is Gujarat's leading educational institute. Accredited by NSDC and ISO, we focus on Integrity, Student-Centricity, Innovation, and Unity. Our goal is to equip students with industry-relevant skills and ensure they are employable globally. Join us for a successful career path. Job Description: Faculties guide students, deliver course materials, conduct lectures, assess performance, and provide mentorship. Strong communication skills and a commitment to supporting students are essential. Key Responsibilities: Deliver high-quality lectures on AI, Machine Learning, and Data Science . Design and update course materials, assignments, and projects. Guide students on hands-on projects, real-world applications, and research work. Provide mentorship and support for student learning and career development. Stay updated with the latest trends and advancements in AI/ML and Data Science. Conduct assessments, evaluate student progress, and provide feedback. Participate in curriculum development and improvements. Skills & Tools: Core Skills: ML, Deep Learning, NLP, Computer Vision, Business Intelligence, AI Model Development, Business Analysis. Programming: Python, SQL (Must), Pandas, NumPy, Excel. ML & AI Tools: Scikit-learn (Must), XGBoost, LightGBM, TensorFlow, PyTorch (Must), Keras, Hugging Face. Data Visualization: Tableau, Power BI (Must), Matplotlib, Seaborn, Plotly. NLP & CV: Transformers, BERT, GPT, OpenCV, YOLO, Detectron2. Advanced AI: Transfer Learning, Generative AI, Business Case Studies. Education & Experience Requirements: Bachelor's/Master’s/Ph.D. in Computer Science, AI, Data Science, or a related field. Minimum 1+ years of teaching or industry experience in AI/ML and Data Science. Hands-on experience with Python, SQL, TensorFlow, PyTorch, and other AI/ML tools. Practical exposure to real-world AI applications, model deployment, and business analytics. Additional Skills: Confident body language and clear communication. Strong classroom management and discipline skills. Punctual, prepared, and passionate about teaching. Open to learning and professional development. Proficient in verbal and written communication. Strong problem-solving, leadership, and decision-making abilities. Positive attitude and ability to work independently. For further information, please feel free to contact 7862813693 us via email at career@rnwmultimedia.edu.in Job Types: Full-time, Permanent Pay: ₹30,000.00 - ₹35,000.00 per month Benefits: Cell phone reimbursement Flexible schedule Leave encashment Paid sick time Paid time off Schedule: Day shift Morning shift Supplemental Pay: Performance bonus Yearly bonus Application Question(s): Current Salary? Experience: Teaching / Mentoring: 1 year (Required) AI: 1 year (Required) ML: 1 year (Required) Data science: 1 year (Required) Location: Ahmedabad, Gujarat (Required) Work Location: In person

At Medtronic you can begin a life-long career of exploration and innovation, while helping champion healthcare access and equity for all. You’ll lead with purpose, breaking down barriers to innovation in a more connected, compassionate world. A Day in the Life As a Data Scientist, where you will develop and deploy machine learning models, conduct advanced analytics, and translate data-driven insights into business value. You will work closely with Finance, Engineering, and Business teams to drive data science initiatives and enhance decision-making. Data Scientist – Global Finance Analytics COE Careers that Change Lives Join our Global Finance Analytics Center of Excellence (COE) as a Data Scientist , where you will develop and deploy machine learning models, conduct advanced analytics, and translate data-driven insights into business value. You will work closely with Finance, Engineering, and Business teams to drive data science initiatives and enhance decision-making. This role requires an average of 2-3 days per week of overlapping work hours with the USA team to ensure seamless collaboration. A Day in the Life As a Data Scientist , you will: Develop and deploy AI/ML models for forecasting, anomaly detection, and optimization in financial and business analytics. Work with structured and unstructured data, ensuring data quality, feature engineering, and model interpretability. Collaborate with Data Engineers to build scalable data pipelines and integrate machine learning solutions into production systems. Perform exploratory data analysis (EDA) and statistical modeling to uncover insights and trends. Optimize algorithms for performance, scalability, and business relevance. Present complex findings in an understandable and actionable manner to senior stakeholders. Continuously explore new AI/ML methodologies and tools to enhance analytical capabilities. Must Have: Minimum Requirements Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field. 5+ years of experience in AI/ML, predictive modeling, and statistical analysis. Strong proficiency in Python, SQL, and cloud platforms (Azure, AWS, or GCP). Experience with machine learning frameworks such as TensorFlow, Scikit-Learn, PyTorch, or XGBoost. Exposure to financial data modeling and analytics. Strong problem-solving and critical-thinking skills. Nice to Have Experience working with Snowflake and large-scale data environments. Knowledge of NLP, deep learning, and AI-driven automation. Familiarity with Power BI for advanced data visualization. Physical Job Requirements The above statements are intended to describe the general nature and level of work being performed by employees assigned to this position, but they are not an exhaustive list of all the required responsibilities and skills of this position. Benefits & Compensation Medtronic offers a competitive Salary and flexible Benefits Package A commitment to our employees lives at the core of our values. We recognize their contributions. They share in the success they help to create. We offer a wide range of benefits, resources, and competitive compensation plans designed to support you at every career and life stage. About Medtronic We lead global healthcare technology and boldly attack the most challenging health problems facing humanity by searching out and finding solutions. Our Mission — to alleviate pain, restore health, and extend life — unites a global team of 95,000+ passionate people. We are engineers at heart— putting ambitious ideas to work to generate real solutions for real people. From the R&D lab, to the factory floor, to the conference room, every one of us experiments, creates, builds, improves and solves. We have the talent, diverse perspectives, and guts to engineer the extraordinary. Learn more about our business, mission, and our commitment to diversity here Show more Show less

Data Scientist Location: Pune (Baner) - Onsite, with possible options of Hybrid Contract: Full-time Salary: Competitive depending on experience. About Protect Group: Protect Group, established in 2016, is an innovative global technology leader enhancing customer experiences and revenue opportunities for businesses through AI-driven solutions. With over 400 partners across 75+ countries, we provide an intuitive widget that seamlessly integrates with online sales platforms, dramatically improving customer satisfaction and boosting ancillary revenue. Our culture is defined by ambition, innovation, and excellence—our Protect People embody these values, making a significant impact across sectors including travel, hospitality, transportation, events, and financial services. Role Overview: We are seeking a talented Data Scientist to play a central role in our global data team. You'll lead analytical initiatives, driving experimentation and optimisation in pricing strategies, significantly influencing our product insights and commercial decision-making. You’ll leverage your expertise in advanced analytics, machine learning, and statistical modelling to derive actionable insights from complex datasets. Key Responsibilities: Analyse large online datasets to uncover valuable insights into consumer behaviour, price elasticity, and revenue optimisation. Collaborate with Product, Technology, Marketing and Sales teams. Contribute insights towards the development and refinement of predictive models used to forecast demand and optimise pricing and content. Create clear and intuitive dashboards and visualisations to communicate insights effectively, facilitating strategic business decisions. Act as a data analytics specialist, encouraging a culture of informed, data-driven decision-making throughout the organisation. Required Skills & Experience: Extensive experience conducting data analysis within relevant sectors. Proficiency in SQL, Python, and data science libraries such as sklearn, XGBoost, and CatBoost. Experience with Azure, MLOps, and API frameworks. Strong understanding of statistical methods, probability theory, pricing optimisation, and elasticity modelling. Expertise with data visualisation tools (e.g., Tableau). Exceptional analytical and creative problem-solving skills, with meticulous attention to detail. Excellent communication skills—capable of articulating complex analytical findings clearly and effectively. Adaptable, innovative, and self-driven, comfortable in fast-paced, agile environments. Why Protect Group? Join a rapidly scaling tech company revolutionising global industries. Lead impactful analyses that directly shape strategic decisions and commercial outcomes. Work within a talented team dedicated to innovation and continuous improvement. Ready to Join Us? If you're passionate about analytics and keen to drive meaningful insights, we want to hear from you! Submit your CV today and share how you'll contribute to Protect Group’s continued success. ***Please note we will be considering those who are currently residing in Pune first. Show more Show less

Senior Applied & Data scientist Hyderabad, Telangana, India Date posted Jun 16, 2025 Job number 1830452 Work site Up to 50% work from home Travel 0-25 % Role type Individual Contributor Profession Research, Applied, & Data Sciences Discipline Data Science Employment type Full-Time Overview Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. The Defender Experts (DEX) Research team is at the forefront of Microsoft’s threat protection strategy, combining world-class hunting expertise with AI-driven analytics to protect customers from advanced cyberattacks. Our mission is to move protection left—disrupting threats early, before damage occurs—by transforming raw signals into intelligence that powers detection, disruption, and customer trust. We’re looking for a passionate and curious Data Scientist to join this high-impact team. In this role, you'll partner with researchers, hunters, and detection engineers to explore attacker behavior, operationalize entity graphs, and develop statistical and ML-driven models that enhance DEX’s detection efficacy. Your work will directly feed into real-time protections used by thousands of enterprises and shape the future of Microsoft Security. This is an opportunity to work on problems that matter—with cutting-edge data, a highly collaborative team, and the scale of Microsoft behind you. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Qualifications Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field 6+ years of experience applying data science or machine learning in a real-world setting, preferably in security, fraud, risk, or anomaly detection Proficiency in Python and/or R, with hands-on experience in data manipulation (e.g., Pandas, NumPy), modeling (e.g., scikit-learn, XGBoost), and visualization (e.g., matplotlib, seaborn) Strong foundation in statistics, probability, and applied machine learning techniques Experience working with large-scale datasets, telemetry, or graph-structured data Ability to clearly communicate technical insights and influence cross-disciplinary teams Demonstrated ability to work independently, take ownership of problems, and drive solutions end-to-end Responsibilities Design and develop data-driven models and algorithms to identify emerging attacker behavior, anomalies, and threat patterns at scale Build and operationalize statistical/ML systems that power early-stage detection, disruption scoring, and alert prioritization within DEX workflows Analyze high-dimensional security telemetry (e.g., token usage, entity relationships, campaign data) to derive signal enrichment and protection insights Collaborate closely with security researchers, threat hunters, and engineers to translate hypotheses into deployable detection logic Lead data investigations on false positives, missed threats, or campaign-level attack patterns to inform detection strategy and service improvement Contribute to the design of entity-based graph pipelines and verdict propagation mechanisms for pre-breach signal interpretation Drive experimentation and model explainability to ensure robustness, interpretability, and operational relevance of developed systems Communicate technical findings to cross-functional stakeholders and influence product and detection roadmap decisions Author internal whitepapers, prototypes, or publications to push the boundaries of applied data science in security Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.  Industry leading healthcare  Educational resources  Discounts on products and services  Savings and investments  Maternity and paternity leave  Generous time away  Giving programs  Opportunities to network and connect Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Job Description About KPMG in India KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada. KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment. TempHtmlFile About KPMG In India KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada. KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment. About Our Financial Crimes specialist teams provide solutions to BFSI clients by conducting model validation testing for AML risk models and frameworks, sanctions screening and transaction monitoring system to ensure efficiency and efficacy of underlying frameworks both functionally and statistically. We are looking to hire colleagues with advance data science and analytics skill to support our financial crimes team. You will play a crucial role in helping clients tackle the multifaceted challenges of financial crime. By utilizing advanced analytics and deep technical knowledge, our team aids top clients in reducing risks associated with financial crime, terrorist financing, and sanctions violations. We also work to enhance their screening and transaction monitoring systems. Our team of specialized analysts ensures that leading financial institutions adhere to industry best practices for robust programs and controls. Through a variety of project experiences, you will develop your professional skills, assisting clients in understanding and addressing complex issues, and implementing top-tier solutions to resolve identified problems. Minimum work experience: 3+ years of advance analytics Preferred experience: 1+ years in AML model validation Responsibilities Support functional SME teams to build data driven Financial Crimes solution Conduct statistical testing of the screening matching algorithms, risk rating models and thresholds configured for detection rules Validate data models of AML systems built on systems such as SAS Viya, Actimize, Lexis Nexis, Napier, etc. Develop, validate, and maintain AML models to detect suspicious activities and transactions. Conduct Above the Line and Below the Line testing Conduct thorough model validation processes, including performance monitoring, tuning, and calibration. Ensure compliance with regulatory requirements and internal policies related to AML model risk management. Collaborate with cross-functional teams to gather and analyze data for model development and validation. P erform data analysis and statistical modeling to identify trends and patterns in financial transactions. Prepare detailed documentation and reports on model validation findings and recommendations. Assist in feature engineering for improvising Gen AI prompts applicable for automation of AML / Screening related investigations Use advanced Machine Learning deployment (e.g. XGBoost) and GenAI approaches Criteria Bachelor’s degree from accredited university 3+ years of complete hands-on experience in Python with an experience in Java, Fast, Django, Tornado or Flask frameworks Working experience in Relational and NoSQL databases like Oracle, MS SQL MongoDB or ElasticSearch Proficiency BI tools such as Power BI, Tableau, etc. Proven experience in data model development and testing Education background in Data Science and Statistics Strong proficiency in programming languages such as Python, R, and SQL. Expertise in machine learning algorithms, statistical analysis, and data visualization tools. Familiarity with regulatory guidelines and standards for AML Experience in AML related model validation and testing Expertise in techniques and algorithms to include sampling, optimization, logistic regression, cluster analysis, Neural Networks, Decision Trees, supervised and unsupervised machine learning Preferred Experiences Validation of AML compliance models such as statistical testing of customer / transaction risk models, screening algorithm testing, etc. Experience with developing proposals (especially new solutions) Experience working AML technology platforms e.g. Norkom, SAS, Lexis Nexis, etc. Hands on experience with data analytics tools using Informatica, Kafka, etc. Equal employment opportunity information KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you. Qualifications TempHtmlFile Bachelor’s degree from accredited university Education background in Data Science and Statistics 3+ years of complete hands-on experience in data science and data analytics Show more Show less

Job Title: Senior Machine Learning Engineer Location: On Site / [Gurgaon, India] Experience: 5+ Years Type: Full-time / Contract About the Role We are looking for an experienced Machine Learning Engineer with a strong background in building, deploying, and scaling ML models in production environments. You will work closely with Data Scientists, Engineers, and Product teams to translate business challenges into data-driven solutions and build robust, scalable ML pipelines. This is a hands-on role requiring a blend of applied machine learning, data engineering, and software development skills. Key Responsibilities Design, build, and deploy machine learning models to solve real-world business problems Work on the end-to-end ML lifecycle: data preprocessing, feature engineering, model selection, training, evaluation, deployment, and monitoring Collaborate with cross-functional teams to identify opportunities for machine learning across products and workflows Develop and optimize scalable data pipelines to support model development and inference Implement model retraining, versioning, and performance tracking in production Ensure models are interpretable, explainable, and aligned with fairness, ethics, and compliance standards Continuously evaluate new ML techniques and tools to improve accuracy and efficiency Document processes, experiments, and findings for reproducibility and team knowledge-sharing Requirements 5+ years of hands-on experience in machine learning, applied data science, or related roles Strong foundation in ML algorithms (regression, classification, clustering, NLP, time series, etc.) Experience with production-level ML deployment using tools like MLflow, Kubeflow, Airflow, FastAPI , or similar Proficiency in Python and libraries like scikit-learn, TensorFlow, PyTorch, XGBoost, pandas, NumPy Experience with cloud platforms (AWS, GCP, or Azure) and containerized environments (Docker, Kubernetes) Strong understanding of software engineering principles and experience with Git, CI/CD, and version control Experience with large datasets, distributed systems (Spark/Databricks), and SQL/NoSQL databases Excellent problem-solving, communication, and collaboration skills Nice to Have Experience with LLMs, Generative AI , or transformer-based models Familiarity with MLOps best practices and infrastructure as code (e.g., Terraform) Experience working in regulated industries (e.g., finance, healthcare) Contributions to open-source projects or ML research papers Why Join Us Work on impactful problems with cutting-edge ML technologies Collaborate with a diverse, expert team across engineering, data, and product Flexible working hours and remote-first culture Opportunities for continuous learning, mentorship, and growth Show more Show less

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

Job Description: Data Scientist - Forecasting We are seeking a highly analytical and experienced Data Scientist to join our Workforce Planning or Analytics team. The ideal candidate will focus on long-term forecasting for contact center operations, leveraging machine learning models and advanced analytics to drive data-informed decisions using Python, SQL and Power BI. You will play a critical role in projecting future contact volumes, resource requirements, and operational trends, directly supporting strategic planning and optimization efforts across the business. Key Responsibilities Analytics & Insights: Analyze historical trends and seasonality to make informed decisions. Apply machine learning and statistical techniques (e.g., ARIMA, Prophet, XGBoost, LSTM, etc.) to improve forecast accuracy over months and years. Conduct in-depth analysis using Excel or Python to identify key drivers of change in volume. Generate Forecast: Generate monthly forecasts for multiple lobs using machine learning models. Monitor and adjust forecasts based on trends, seasonality, and business updates. Forecast assessment: Evaluate forecast accuracy every month and present key findings. Monitor forecast performance, diagnose deviations, and continuously improve model performance using feedback loops and model validation. Stakeholder Collaboration: Present analytical findings and strategic recommendations to stakeholders, especially around critical days or events. Collaborate with cross-functional teams to understand business requirements and deliver analytical solutions Required Skills & Expertise Technical Skills: Proficiency in Excel, SQL and Python for advanced data analysis, data extraction and data manipulation Hands-on experience with data visualization tools (e.g., Tableau, Power BI) is a plus. Analytical Acumen: Advanced knowledge of Time Series forecasting techniques or Contact Center demand volume forecasting. Ability to work with large datasets and extract meaningful insights to generate forecasts Ability to work on ad-hoc requests to support business needs and derive actionable insights Problem-Solving & Communication: Strong problem-solving skills, with the ability to translate complex analytical findings into clear and actionable recommendations. Excellent communication and data storytelling skills; able to influence stakeholders using evidence-based insights Candidate Profile Educational Background: Bachelor’s/Master’s degree in Analytics, Data Science, Economics, Statistics, Engineering, or a related field. Professional Experience: At least 3-5 years of experience in the data analytics with good experience of Time Series Forecasting. Show more Show less

Greetings from Colan Infotech!! Role - Data Scientist Experience - 3+ Years Job Location - Chennai/Bangalore Notice Period - Immediate to 30 Days Primary Skills Needed : AI/ML, Tensorflow, Django, Pytorch, NLP, Image processing,Gen AI,LLM Secondary Skills Needed : Keras, OpenCV, Azure or AWS Job Description:- Practical knowledge and working experience on Statistics and Operation Research methods. Practical knowledge and working experience in tools and frameworks like Flask, PySpark, Pytorch, tensorflow, keras, Databricks, OpenCV, Pillow/PIL, streamlit, d3js, dashplotly, neo4j. Good understanding of how to apply predictive and machine learning techniques like regression models, XGBoost, random forest, GBM, Neural Nets, SVM etc. Proficient with NLP techniques like RNN, LSTM and Attention based models and effectively handle readily available stanford, IBM, Azure, Open AI NLP models. Good understanding of SQL from a perspective of how to write efficient queries for pulling the data from database. Hands on experience on any version control tool (github, bitbucket). Experience of deploying ML models into production environment experience (MLOps) in any one of the cloud platforms like Azure and AWS Comprehend business issues and propose valuable business solutions. Design Factual or AI/profound learning models to address business issues. Design Statistical Models/ML/DL models and deploy them for production. Formulate what information is accessible from where and how to augment it. Develop innovative graphs for data comprehension using d3js, dashplotly and neo4j Show more Show less

Position Title : AI/ML Engineer. Company : Cyfuture India Pvt.Ltd. Industry : IT Services and IT Consulting. Location : Sector 81, NSEZ, Noida (5 Days Work From Office). About Cyfuture Cyfuture is a trusted name in IT services and cloud infrastructure, offering state-of-the-art data center solutions and managed services across platforms like AWS, Azure, and VMWare. We are expanding rapidly in system integration and managed services, building strong alliances with global OEMs like VMWare, AWS, Azure, HP, Dell, Lenovo, and Palo Alto. Position Overview We are hiring an experienced AI/ML Engineer to lead and shape our AI/ML initiatives. The ideal candidate will have hands-on experience in machine learning and artificial intelligence, with strong leadership capabilities and a passion for delivering production-ready solutions. This role involves end-to-end ownership of AI/ML projects, from strategy development to deployment and optimization of large-scale systems. Key Responsibilities Lead and mentor a high-performing AI/ML team. Design and execute AI/ML strategies aligned with business goals. Collaborate with product and engineering teams to identify impactful AI opportunities. Build, train, fine-tune, and deploy ML models in production environments. Manage operations of LLMs and other AI models using modern cloud and MLOps tools. Implement scalable and automated ML pipelines (e., with Kubeflow or MLRun). Handle containerization and orchestration using Docker and Kubernetes. Optimize GPU/TPU resources for training and inference tasks. Develop efficient RAG pipelines with low latency and high retrieval accuracy. Automate CI/CD workflows for continuous integration and delivery of ML systems. Key Skills & Expertise Cloud Computing & Deployment : Proficiency in AWS, Google Cloud, or Azure for scalable model deployment. Familiarity with cloud-native services like AWS SageMaker, Google Vertex AI, or Azure ML. Expertise in Docker and Kubernetes for containerized deployments. Experience with Infrastructure as Code (IaC) using tools like Terraform or CloudFormation. Machine Learning & Deep Learning Strong command of frameworks : TensorFlow, PyTorch, Scikit-learn, XGBoost. Experience with MLOps tools for integration, monitoring, and automation. Expertise in pre-trained models, transfer learning, and designing custom architectures. Programming & Software Engineering Strong skills in Python (NumPy, Pandas, Matplotlib, SciPy) for ML development. Backend/API development with FastAPI, Flask, or Django. Database handling with SQL and NoSQL (PostgreSQL, MongoDB, BigQuery). Familiarity with CI/CD pipelines (GitHub Actions, Jenkins). Scalable AI Systems Proven ability to build AI-driven applications at scale. Handle large datasets, high-throughput requests, and real-time inference. Knowledge of distributed computing : Apache Spark, Dask, Ray. Model Monitoring & Optimization Hands-on with model compression, quantization, and pruning. A/B testing and performance tracking in production. Knowledge of model retraining pipelines for continuous learning. Resource Optimization Efficient use of compute resources : GPUs, TPUs, CPUs. Experience with serverless architectures to reduce cost. Auto-scaling and load balancing for high-traffic systems. Problem-Solving & Collaboration Translate complex ML models into user-friendly applications. Work effectively with data scientists, engineers, and product teams. Write clear technical documentation and architecture reports. (ref:hirist.tech) Show more Show less

Role : Machine Learning Engineer Key Responsibilities Collaborate with data scientists to support end-to-end ML model development, including data preparation, feature engineering, training, and evaluation. Build and maintain automated pipelines for data ingestion, transformation, and model scoring using Python and SQL. Assist in model deployment using CI/CD pipelines (e.g., Jenkins) and ensure smooth integration with production systems. Develop tools and scripts to support model monitoring, logging, and retraining workflows. Work with data from relational databases (RDS, Redshift) and preprocess it for model consumption. Analyze pipeline performance and model behavior; identify opportunities for optimization and refactoring. Contribute to the development of a feature store and standardized processes to support reproducible data science. Required Skills & Experience 1-3 years of hands-on experience in Python programming for data science or ML engineering tasks. Solid understanding of machine learning workflows, including model training, validation, deployment, and monitoring. Proficient in SQL and working with structured data from sources like Redshift, RDS, etc. Familiarity with ETL pipelines and data transformation best practices. Basic understanding of ML model deployment strategies and CI/CD tools like Jenkins. Strong analytical mindset with the ability to interpret and debug data/model issues. Preferred Qualifications Exposure to frameworks like scikit-learn, XGBoost, LightGBM, or similar. Knowledge of ML lifecycle tools (e.g., MLflow, Ray). Familiarity with cloud platforms (AWS preferred) and scalable infrastructure. (ref:hirist.tech) Show more Show less