60 Anomaly Detection Jobs - Page 2

You will be involved in building a machine learning-based anomaly detection system using structured and sequential sensor data. Your main task will be to identify unusual patterns or faults through data modeling and visualization. This internship will provide you with a real-world opportunity to work on machine learning pipelines and understand both supervised and unsupervised approaches to anomaly detection. During this phase, you will focus on offline/static modeling using historical sensor data in tabular and time-series formats. Your primary objectives will include analyzing sensor datasets representing various operational scenarios, applying and evaluating supervised classification models, transitioning into unsupervised anomaly detection approaches, visualizing insights, and documenting findings for technical and non-technical audiences. Your key responsibilities will involve performing data preprocessing tasks such as cleaning, encoding, normalization, and feature engineering. Additionally, you will be required to train and evaluate classification models using Artificial Neural Networks (ANN) and Long Short-Term Memory (LSTM) models for sequence-based classification. You will also explore and implement unsupervised anomaly detection techniques like Isolation Forest, One-Class SVM, and Z-score or IQR-based statistical methods. Analyzing and visualizing model outputs using confusion matrices, anomaly heatmaps, and time-series plots will also be part of your responsibilities. Optionally, you may also be tasked with building a lightweight dashboard (e.g., using Streamlit) to present findings. TechnoExcel is the leading training and consulting company in Hyderabad offering data analytics solutions.,

Capgemini Invent Capgemini Invent is the digital innovation, consulting and transformation brand of the Capgemini Group, a global business line that combines market leading expertise in strategy, technology, data science and creative design, to help CxOs envision and build whats next for their businesses. Your Role Edge AI Data Scientists will be responsible for designing, developing, and validating machine learning modelsparticularly in the domain of computer visionfor deployment on edge devices. This role involves working with data from cameras, sensors, and embedded platforms to enable real-time intelligence for applications such as object detection, activity recognition, and visual anomaly detection. The position requires close collaboration with embedded systems and AI engineers to ensure models are lightweight, efficient, and hardware-compatible. Candidate Requirements Education Bachelor"s or Masters degree in Data Science, Computer Science, or a related field. Experience 3+ years of experience in data science or machine learning with a strong focus on computer vision. Experience in developing models for edge deployment and real-time inference. Familiarity with video/image datasets and deep learning model training. Skills Proficiency in Python and libraries such as OpenCV, PyTorch, TensorFlow, and FastAI. Experience with model optimization techniques (quantization, pruning, etc.) for edge devices. Hands-on experience with deployment tools like TensorFlow Lite, ONNX, or OpenVINO. Strong understanding of computer vision techniques (e.g., object detection, segmentation, tracking). Familiarity with edge hardware platforms (e.g., NVIDIA Jetson, ARM Cortex, Google Coral). Experience in processing data from camera feeds or embedded image sensors. Strong problem-solving skills and ability to work collaboratively with cross-functional teams. Your Profile Responsibilities Develop and train computer vision models tailored for constrained edge environments. Analyze camera and sensor data to extract insights and build vision-based ML pipelines. Optimize model architecture and performance for real-time inference on edge hardware. Validate and benchmark model performance on various embedded platforms. Collaborate with embedded engineers to integrate models into real-world hardware setups. Stay up-to-date with state-of-the-art computer vision and Edge AI advancements. Document models, experiments, and deployment configurations. What you will love about working here We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance. At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities. Equip yourself with valuable certifications in the latest technologies such as Generative AI. About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and iCa sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of 22.5 billion.

To ensure youre set up for success, you will bring the following skillset & experience: You have 4+ years of experience with application development using Python/Fast API, Java, RESTful services, high-performance, and multi-threading. Bachelors or masters degree in computer science, Statistics, Mathematics, Data Science, or a related field. Full Stack Developer with emphasis on [Python, Relational (PostGres) and Vector databases (FAISS, Weaviate, Milvus), Cloud Platforms/Services (AWS, GCP, Azure)] Good to have Frontend Development (Angular, React and SSR) experience Experience with machine learning frameworks and libraries (PyTorch, TensorFlow, scikit-learn). Experience with LangChain, LangGraph and LlamaIndex and LiteLLM for building LLM-powered applications Understanding of time-series modeling, anomaly detection, or clustering techniques. Experience with data engineering (ETL pipelines, data warehouses, etc.) and Hands-on exposure to model tracking (MLflow), serving (FastAPI, vLLM), and container orchestration frameworks (Kubernetes, DockerSwarm)

As a Cloud FinOps consultant with 8-10 years of experience, you will be responsible for developing and implementing a robust program for cloud cost management. This includes designing a service-based cost allocation and classification strategy, tracking and managing cloud costs, setting cloud services rates, and generating consumption and show back/chargeback reports from both the provider and consumer perspective. You should be an experienced Cloud FinOps Practitioner proficient in working primarily on Azure and AWS platforms for Cloud Optimization & Cost savings. Possessing a certification as a FinOps Practitioner will be an added advantage. Your role will involve creating a cloud cost optimization framework and Governance mechanism. In this position, you will take ownership of Cost Analysis, Reviewing Recommendations, creating budgeting alerts, purchasing reservations/savings plans, tagging, anomaly detection, and forecasting spend. Additionally, you should have experience in rightsizing computer services, identifying unused resources, and implementing AHUB. Join us in this challenging role where you will play a crucial part in optimizing cloud costs and enhancing overall efficiency in cloud management.,

We are looking for someone who is enthusiastic to contribute to the implementation of a metadata-driven platform managing the full lifecycle of batch and streaming Big Data pipelines. This role involves applying ML and AI techniques in data management, such as anomaly detection for identifying and resolving data quality issues and data discovery. The platform facilitates the delivery of Visa's core data assets to both internal and external customers. You will provide Platform-as-a-Service offerings that are easy to consume, scalable, secure, and reliable using open source-based Cloud solutions for Big Data technologies. Working at the intersection of infrastructure and software engineering, you will design and deploy data and pipeline management frameworks using open-source components like Hadoop, Hive, Spark, HBase, Kafka streaming, and other Big Data technologies. Collaboration with various teams is essential to build and maintain innovative, reliable, secure, and cost-effective distributed solutions. Facilitating knowledge transfer to the Engineering and Operations team, you will work on technical challenges and process improvements with geographically distributed teams. Your responsibilities will include designing and implementing agile-innovative data pipeline and workflow management solutions that leverage technology advances for cost reduction, standardization, and commoditization. Driving the adoption of open standard toolsets to reduce complexity and support operational goals for increasing automation across the enterprise is a key aspect of this role. As a champion for the adoption of open infrastructure solutions that are fit for purpose, you will keep technology relevant. The role involves spending 80% of the time writing code in different languages, frameworks, and technology stacks. At Visa, your uniqueness is valued. Working here provides an opportunity to make a global impact, invest in your career growth, and be part of an inclusive and diverse workplace. Join our global team of disruptors, trailblazers, innovators, and risk-takers who are driving economic growth worldwide, moving the industry forward creatively, and engaging in meaningful work that brings financial literacy and digital commerce to millions of unbanked and underserved consumers. This position is hybrid, and the expectation of days in the office will be confirmed by your hiring manager. **Basic Qualifications**: - Minimum of 6 months of work experience or a bachelor's degree - Bachelor's degree in Computer Science, Computer Engineering, or a related field - Good understanding of data structures and algorithms - Good analytical and problem-solving skills **Preferred Qualifications**: - 1 or more years of work experience or an Advanced Degree (e.g., Masters) in Computer Science - Excellent programming skills with experience in at least one of the following: Python, Node.js, Java, Scala, GoLang - MVC (model-view-controller) for end-to-end development - Knowledge of SQL/NoSQL technology. Familiarity with Databases like Oracle, DB2, SQL Server, etc. - Proficiency in Unix-based operating systems and bash scripts - Strong communication skills, including clear and concise written and spoken communications with professional judgment - Team player with excellent interpersonal skills - Demonstrated ability to lead and navigate through ambiguity **Additional Information**:,

You are an experienced Lead Data Scientist with a minimum of 8 years of professional experience, including at least 6 years in a data science role. Your expertise lies in statistical modeling, machine learning, deep learning, and GenAI. Proficiency in Python is a must, along with hands-on experience in optimizing code for performance. You excel in data preprocessing, feature engineering, data visualization, hyperparameter tuning, and have a solid understanding of database concepts, especially while working with large datasets. You have experience deploying and scaling machine learning models in a production environment, along with familiarity with machine learning operations (MLOps) and related tools. Your knowledge extends to Generative AI concepts and LLM finetuning, supported by excellent communication and collaboration skills. Your responsibilities as a Lead Data Scientist include guiding and mentoring a high-performance team on the latest technology landscape, patterns, and design standards. You provide strategic direction and technical leadership for AI initiatives, leading the design and architecture of complex AI systems. Your role involves developing and deploying machine learning/deep learning models to address key business challenges, applying various techniques in statistical modeling, data preprocessing, feature engineering, and more. You are proficient in areas such as computer vision, predictive analytics, natural language processing, time series analysis, and recommendation systems. Furthermore, you design and optimize data pipelines for model training and deployment, utilizing model serving frameworks and APIs for integration with other systems. Your qualifications include a Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Your primary skills encompass Python, Data Science concepts, Pandas, NumPy, Matplotlib, Artificial Intelligence, Statistical Modeling, Machine Learning, Natural Language Processing (NLP), Deep Learning, Model Serving Frameworks, MLOps, Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems, Generative AI, and proficiency in Cloud Computing Platforms. Your secondary skills involve expertise in designing scalable and efficient model architectures, the ability to assess and forecast financial requirements of data science projects, and strong communication skills for conveying technical concepts to stakeholders. As a Lead Data Scientist, you stay updated with the latest advancements in data science and machine learning, particularly in generative AI, to evaluate their potential applications and serve as a primary point of contact for client managers.,

As a Data Scientist at our organization, you will be applying your expertise in artificial intelligence by utilizing machine learning, data mining, and information retrieval to design, prototype, and construct advanced analytics engines and services for next-generation applications. Your role will involve collaborating with business partners to define technical problem statements and hypotheses, developing analytical models that align with business decisions, and integrating them into data products or tools with a cross-functional team. Your responsibilities will include: - Collaborating with business partners to devise innovative solutions using cutting-edge techniques and tools - Effectively communicating the analytics approach to address objectives - Advocating for data-driven decision-making and emphasizing the importance of problem-solving methodologies - Leading analytic approaches and integrating them into applications with data engineers, business leads, analysts, and developers - Creating scalable, dynamic, and interpretable models for analytic data products - Engineering features by leveraging internal and external data sources - Sharing your passion for Data Science within the enterprise community and contributing to the development of processes, frameworks, and standards - Collaborating, coaching, and learning with a team of experienced Data Scientists - Staying updated with the latest trends and ideas in the field through conferences and community engagements Desired Skills: - Bachelor's degree required, MS or PhD preferred - Bachelor's in Data Science, Computer Science, Engineering, Statistics, and 5+ years of experience OR Graduate degree in a quantitative discipline with demonstrated Data Science skills and 2+ years of work experience - Proficiency in Python for working with DataFrames - Proficiency in writing complex SQL queries - Experience with Machine Learning for clustering, classification, regression, anomaly detection, simulation, and optimization on large datasets - Ability to merge and transform disparate internal and external data sets to create new features - Experience with Big Data technologies such as Spark, Cloud AI platforms, and containerization - Experience in supporting deployment, monitoring, maintenance, and enhancement of models - Familiarity with data visualization tools like Tableau, Plotly, etc. Digital Experience/Individual Skills: - Excellent communication and collaboration skills to understand business needs and deliver solutions - Proven ability to prioritize tasks and manage time effectively to achieve outstanding results - Efficient learning capability to tackle new business domains and problems - Critical thinking and skepticism regarding the validity and biases of data - Intellectual curiosity and humility to leverage expertise and collaborate effectively - Strong organizational skills with attention to detail and accuracy - Ability to mentor, coach, and work closely with business partners, analysts, and team members,

As a Data Analyst at our company based in Trivandrum, you will be responsible for analyzing large volumes of log data from NGINX server logs to identify user behavior patterns, anomalies, and security events. Your role will involve interpreting various fields such as IP addresses, geolocation data, user agents, request paths, status codes, and request times to derive meaningful insights. Collaboration with AI engineers is crucial as you will work together to propose relevant features based on log behavior and traffic patterns. Your responsibilities will include validating engineered features, conducting exploratory data analysis, and ensuring the quality and alignment of feature logic with real-world HTTP behavior and use cases. Furthermore, you will be involved in developing data visualizations to represent time-series trends, geo-distributions, and traffic behavior. Your collaboration with the frontend/dashboard team will be essential in defining and testing visual requirements and anomaly indicators for real-time dashboards. In addition to your analytical tasks, you will also be responsible for identifying and addressing gaps, inconsistencies, and errors in raw logs to ensure data quality. Creating documentation that explains observed behavioral patterns, feature assumptions, and traffic insights for knowledge sharing within the ML and security team will also be part of your role. The minimum qualifications for this position include a Bachelor's degree in Computer Science, Information Systems, Data Analytics, Cybersecurity, or a related field, along with at least 2 years of experience in data analysis or analytics roles. Proficiency in SQL, Elasticsearch queries, Python for data analysis, and experience working with web server logs or structured event data are required. Strong analytical thinking skills are essential to break down complex log behavior into patterns and outliers. It would be beneficial if you have familiarity with web security concepts, experience with log analytics platforms, an understanding of feature engineering concepts in ML pipelines, or experience working on anomaly detection or security analytics systems. This is a full-time position with benefits such as health insurance and Provident Fund, with a day shift schedule from Monday to Friday. If you possess the necessary qualifications and experience, we look forward to receiving your application.,

The Healthcare Analytics Specialist position based in Gurugram requires 3 to 5 years of experience. You will be responsible for developing, maintaining, and optimizing data pipelines, including ingestion, transformation, and loading of internal and external sources. Collaboration with Operations is essential to design scalable, secure, and high-performing data workflows. Best practices in data governance, version control, security, and documentation must be implemented. Analytical models for cost, quality, and utilization metrics will be built and maintained using tools like Python, R, or SQL-based BI tools. Reports will be developed to communicate findings to stakeholders across the organization. Ingesting and preprocessing third-party data from various sources, ensuring compliance with transparency requirements and designing automated workflows for data validation are key responsibilities. Data quality assurance through validation checks, audits, and anomaly detection frameworks is crucial. Compliance with healthcare regulations such as HIPAA, HITECH, and data privacy requirements must be maintained. Participation in internal and external audits of data processes is expected. Continuous improvement and thought leadership are encouraged to enhance data processes, adopt new technologies, and promote a data-driven culture within the organization. Mentoring junior analysts and sharing best practices in data analytics, reporting, and pipeline development are part of the role. Required qualifications include a Bachelor's degree in health informatics, Data Science, Computer Science, Statistics, or a related field. Proficiency in data integration & ETL, databases & cloud, BI & visualization, and healthcare domain expertise is necessary. Analytical & problem-solving skills, soft skills, and strong project management abilities are also required. Preferred qualifications include advanced degrees, experience with healthcare cost transparency regulations, familiarity with DataOps or DevOps practices, certification in BI or data engineering, and experience in data stewardship programs & leading data governance initiatives. Joining this position offers opportunities for innovation through advanced analytics projects, growth by leading initiatives and mentoring others, and working in a supportive culture that values open communication, knowledge sharing, and continuous learning.,

Please Note- Its 6 days WFO from Client location in Kolkata Role & responsibilities Data Science & AI Specialist in Kolkata requires strong programming skills in Python and experience with AI/ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch, XGBoost). Proficiency in Jupyter and Databricks, along with experience in time-series modeling, advanced regression, anomaly detection, and optimization algorithms , is necessary. An understanding of energy systems, including renewables, grid infrastructure, and smart meters, is advantageous. Candidates should be familiar with cloud platforms (AWS, Azure, GCP) and MLOps tools for model deployment and monitoring, as well as data visualization tools (Power BI) and version control (Git). The ideal candidate will have a bachelors or master’s degree in relevant fields and 2+ years of experience in AI and data science projects , preferably in the energy domain Kindly note that resource must travel to Kolkata Sector 5 client office daily ( No work from home ) and 6 Days a week working

We are looking for a highly experienced Senior AI/ML Engineer with a strong background in cloud infrastructure and IoT to join our dynamic team in Ahmedabad. As an ML Engineer/MLOps Engineer, your primary responsibility will be to lead the design, development, and deployment of AI/ML solutions on cloud platforms, integrate IoT technologies, and drive innovation in intelligent systems. Your role will involve leading the end-to-end development and deployment of AI/ML solutions on cloud platforms such as AWS for applications like predictive analytics, anomaly detection, and intelligent automation. You will also be responsible for integrating IoT sensors, devices, and protocols like MQTT into AI/ML solutions to enable intelligent decision-making, remote monitoring, and control in IoT environments. Additionally, you will architect and optimize cloud infrastructure for AI workloads, design data pipelines for IoT data ingestion, and train machine learning models for various tasks using state-of-the-art algorithms and frameworks like PyTorch. Collaboration with cross-functional teams, including data scientists, software engineers, and product managers, is essential to define project requirements, develop prototypes, and deliver scalable AI/ML solutions that align with business objectives. You will need to implement algorithms and models proficiently using programming languages like Python, R, or Java and leverage relevant libraries and frameworks for computer vision tasks. Furthermore, you should have a Bachelor's or Master's degree in Computer Science, Engineering, or related field, along with 3-5 years of proven experience as an AI/ML Engineer. Strong programming skills in Python, familiarity with AI/ML libraries/frameworks, IoT development, containerization, and serverless computing are crucial requirements for this role. A deep understanding of machine learning algorithms, model training, validation, and deployment best practices is also essential. If you are willing to relocate to Ahmedabad and meet the educational and experience requirements mentioned above, we encourage you to apply for this full-time ML Engineer/MLOps Engineer position.,

We are looking for a highly skilled AI and 3D Computer Vision Developer to join our innovative team. Your main focus will be on developing advanced algorithms for spatial perception, 3D computer vision, and sensor data analytics. As part of this role, you will be responsible for designing and implementing cutting-edge AI solutions for object detection, tracking, and scene understanding. Additionally, you will work on sensor data analytics for various applications. Your expertise in machine learning, deep learning, and computer vision will be crucial in creating real-time applications. Strong proficiency in spatial analytics, sensor fusion, and data-driven problem-solving is essential for success in this role. If you are passionate about pushing the boundaries of AI and 3D perception, we are excited to hear from you! To be considered for this position, you should have a minimum of 4+ years of overall work experience. Ideal candidates will have experience in areas such as spatial or scene understanding, data analytics, and advanced AI technologies. This includes expertise in detection, tracking, segmentation, recognition, handling large volumes of sensor data, and hands-on experience with Large Language Models, Generative AI, and other cutting-edge artificial intelligence technologies.,

Key Responsibilities Extract and analyze data from company databases to drive the optimization and enhancement of product development and marketing strategies. Analyze large datasets to uncover trends, patterns, and insights that can influence business decisions. Leverage predictive and AI/ML modeling techniques to enhance and optimize customer experience, boost revenue generation, improve ad targeting, and more. Design, implement, and optimize machine learning models for a wide range of applications such as predictive analytics, natural language processing, recommendation systems, and more. Conduct experiments to fine-tune machine learning models and evaluate their performance using appropriate metrics. Deploy machine learning models into production environments, ensuring scalability Qualifications Bachelor's, Master's or Ph.D in Computer Science, Data Science, Mathematics, Statistics, or a related field. 2+ years of experience in Analytics, Machine learning, Deep learning. Proficiency in programming languages such as Python, and familiarity with machine learning libraries (e.g., Numpy, Pandas, TensorFlow, Keras, PyTorch, Scikit-learn). Strong experience with data wrangling, cleaning, and transforming raw data into structured, usable formats. Hands-on experience in developing, training, and deploying machine learning models for various applications (e.g., predictive analytics, recommendation systems, anomaly detection). In-depth understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning) and their appropriate use cases. Experience with model evaluation techniques (e.g., cross-validation, A/B testing, performance metrics). Experience with cloud platforms (AWS, GCP, Azure) for model deployment and scalal Proficiency in data processing and manipulation techniques. Excellent problem-solving skills and the ability to work effectively in a collabor environment. Strong communication skills to convey complex technical concepts to non-tech stakeholders. Good To Have Experience in the [banking/financial services/industry-specific] sector. Familiarity with cloud-based machine learning platforms such as Azure, AWS, or GCP. Skills: recommendation systems,pytorch,cloud,anomaly detection,numpy,python,data cleaning,deep learning,predictive analytics,a/b testing,machine learning,pandas,tensorflow,scikit-learn,data wrangling,cloud platforms (aws, gcp, azure),model evaluation techniques,cross-validation,keras,machine learning models,

The company Armada is an edge computing startup that specializes in providing computing infrastructure to remote areas with limited connectivity and cloud infrastructure. They also focus on processing data locally for real-time analytics and AI at the edge. Armada is dedicated to bridging the digital divide by deploying advanced technology infrastructure rapidly. As they continue to grow, they are seeking talented individuals to join them in achieving their mission. As a DevOps Lead at Armada, you will play a crucial role in integrating AI-driven operations into the DevOps practices of the company. Your responsibilities will include leading a DevOps team, designing scalable systems, and implementing intelligent monitoring, alerting, and self-healing infrastructure. The role requires a strategic mindset and hands-on experience with a focus on Ops AI. This position is based at the Armada office in Trivandrum, Kerala. As the DevOps Lead, you will lead the DevOps strategy with a strong emphasis on AI-enabled operational efficiency. You will architect and implement CI/CD pipelines integrated with machine learning models and analytics. Additionally, you will develop and manage infrastructure as code using tools like Terraform, Ansible, or CloudFormation. Collaboration is key in this role, as you will work closely with data scientists, developers, and operations teams to deploy and manage AI-powered applications. You will also be responsible for enhancing system observability through intelligent dashboards and real-time metrics analysis. Furthermore, you will mentor DevOps engineers and promote best practices in automation, security, and performance. To be successful in this role, you should have a Bachelor's or Master's degree in Computer Science, Engineering, or a related field. You should also have at least 7 years of DevOps experience with a minimum of 2 years in a leadership role. Proficiency in cloud infrastructure management and automation is essential, along with experience in AIOps platforms and tools. Strong scripting abilities, familiarity with CI/CD tools, and expertise in containerization and orchestration are also required. Preferred qualifications include knowledge of MLOps, experience with serverless architectures, and certification in cloud platforms. Demonstrable experience in building and integrating software and hardware for autonomous or robotic systems is a plus. Strong analytical skills, time-management abilities, and effective communication are highly valued for this role. In return, Armada offers a competitive base salary along with equity options for India-based candidates. If you are a proactive individual with a growth mindset, strong problem-solving skills, and the ability to thrive in a fast-paced environment, you may be a great fit for this position at Armada. Join the team and contribute to the success and growth of the company while working collaboratively towards achieving common goals.,

About the Role We're looking for an experienced Data Scientist with deep expertise in financial crime analytics, especially anti-money laundering (AML). This role is all about crafting and delivering tailored solutions that directly address the complex and evolving needs of AML teams across the banking and financial services industry. You'll build high-quality, production-grade code, partner closely with customers, and bring a strong product mindset to how we develop and expand our financial crime use case library. Your work will serve as a foundational layer for AML teams to detect, investigate, and prevent financial crime with greater speed and accuracy. What You'll Do Design and implement targeted AML and financial crime use cases based on client needs and risk typologies Translate regulatory requirements and fraud/AML patterns into technical solutions Write high-quality, maintainable code with an eye toward scalability and performance Produce clear documentation to support operationalization, audit, and model explainability Collaborate directly with clients and internal teams to refine use case objectives and delivery Bring a product-driven approach to solution development, identifying features and improvements over time What You Bring Hands-on experience in financial crime analytics, particularly AML typology development and deployment Prior work in banking or regulated financial environments, with familiarity around compliance and risk Solid programming skills in Python and/or similar, including data pipeline and modeling tools Experience with statistical analysis and machine learning for anomaly detection or behavior modeling Comfortable interacting with customers and translating business challenges into technical design A sharp, iterative mindset focused on delivering measurable results and sustainable solutions Why Join Us Help shape the next generation of data-driven AML tools and capabilities Partner directly with top-tier institutions to combat complex financial threats Work in a fast-moving environment that values clarity, ownership, and technical craft Career Level - IC4

Looking for a candidate with R&D experience in software product development, image analysis, computer vision, ML models, neural networks, image forensics, and algorithm design for classification, detection, and anomaly detection tasks.

Template Job Title - Decision Science Practitioner Analyst S&C GN Management Level :Senior Analyst Location:Bangalore/ Kolkata Must have skills: Collibra Data Quality - data profiling, anomaly detection, reconciliation, data validation, Python, SQL Good to have skills: PySpark, Kubernetes, Docker, Git Job Summary : We are seeking a highly skilled and motivated Data Science cum Data Engineer Senior Analyst to lead innovative projects and drive impactful solutions in domains such as Consumer Tech , Enterprise Tech , and Semiconductors . This role combines hands-on technical expertise , and client delivery management to execute cutting-edge projects in data science & data engineering Key Responsibilities Data Science and Engineering Implement and manage end to end Data Quality frameworks using Collibra Data Quality (CDQ). This includes requirement gathering from the client, code development on SQL, Unit testing, Client demos, User acceptance testing, documentation etc. Work extensively with business users, data analysts, and other stakeholders to understand data quality requirements and business use cases. Developdata validation, profiling, anomaly detection, and reconciliation processes. WriteSQL queries for simple to complex data quality checks . Python, and PySpark scripts to support data transformation and data ingestion. Deploy and manage solutions on Kubernetes workloads for scalable execution. Maintain comprehensivetechnical documentation of Data Quality processes and implemented solutions. Work in an Agile environment , leveraging Jira for sprint planning and task management. Troubleshoot data quality issues and collaborate with engineering teams for resolution. Provide insights forcontinuous improvement in data governance and quality processes. Build and manage robust data pipelines using Pyspark and Python to read and write from databases such as Vertica and PostgreSQL. Optimize and maintain existing pipelines for performance and reliability. Build custom solutions using Python, including FastAPI applications and plugins for Collibra Data Quality. Oversee the infrastructure of the Collibra application in Kubernetes environment, perform upgrades when required, and troubleshoot and resolve any Kubernetes issues that may affect the application's operation. Deploy and manage solutions, optimize resources for deployments in Kubernetes, including writing YAML files and managing configurations Build and deploy Docker images for various use cases, ensuring efficient and reusable solutions. Collaboration and Training Communicate effectively with stakeholders to align technical implementations with business objectives. Provide training and guidance to stakeholders on Collibra Data Quality usage and help them build and implement data quality rules. Version Control and Documentation Use Git for version control to manage code and collaborate effectively. Document all implementations, including data quality workflows, data pipelines, and deployment processes, ensuring easy reference and knowledge sharing. Database and Data Model Optimization Design and optimize data models for efficient storage and retrieval. Required Qualifications Experience:4+ years in data science Education:B tech, M tech in Computer Science, Statistics, Applied Mathematics, or related field Industry Knowledge:Preferred experience in Consumer Tech, Enterprise Tech, or Semiconductors but not mandatory Technical Skills Programming: Proficiency in Python , SQL for data analysis and transformation. Tools :Hands-on experience with Collibra Data Quality (CDQ) or similar Data Quality tools (e.g., Informatica DQ, Talend, Great Expectations, Ataccama, etc.). Experience working with Kubernetes workloads. Experience with Agile methodologies and task tracking using Jira. Preferred Skills Strong analytical and problem-solving skills with a results-oriented mindset. Good communication, stakeholder management & requirement gathering capabilities. Additional Information: - The ideal candidate will possess a strong educational background in quantitative discipline and experience in working with Hi-Tech clients - This position is based at our Bengaluru (preferred) and Kolkata office. About Our Company | AccentureQualification Experience: 4+ years in data science Educational Qualification:B tech, M tech in Computer Science, Statistics, Applied Mathematics, or related field

About the Team We are looking for a passionate AI/ML Engineer with a strong background in Generative AI, NLP, and large-scale data systems. As an individual contributor (IC3/IC4), youll work at the intersection of research and productizationbuilding intelligent, scalable, and secure AI systems that power next-gen enterprise experiences across Nutanix platforms. This is your opportunity to design and deliver cutting-edge AI capabilities that simplify cloud infrastructure, elevate data insights, and transform user interactions. Your Role such as intelligent assistants, autonomous infrastructure, anomaly detection, recommendation systems, and more. Contribute to and/or lead initiatives to fine-tune and optimize LLMs (e.g., LLaMA, Mistral, GPT) using Nutanix-specific datasets. Work on RAG pipelines, embeddings, vector DBs, prompt engineering, and responsible AI guardrails. Collaborate with product managers, designers, and platform engineers to integrate AI features seamlessly into Nutanix products. Own the end-to-end ML lifecycle: from data engineering, experimentation, training, and evaluation to deployment and monitoring. Build reusable ML components, services, and APIs with a focus on scalability, observability, and reliability. Contribute to internal AI platforms/tools and best practices, including model evaluation frameworks and GPU/accelerator optimization. Stay on top of emerging AI/ML research and tools and help drive innovation across the org. What You Will Bring Basic Requirements (IC3/IC4) Bachelor's or Masters in Computer Science, Machine Learning, or related field. 36 years (IC3) or 69 years (IC4) of industry experience in AI/ML with at least 12 years in Generative AI and LLMs. Strong programming skills in Python, familiarity with ML/AI libraries (PyTorch, TensorFlow, Hugging Face, LangChain, etc.). Experience with fine-tuning LLMs, prompt engineering, embeddings, and working with vector databases (e.g., FAISS, Pinecone, Weaviate). Hands-on experience in ML Ops: data versioning, model serving, and monitoring. Solid understanding of NLP techniques, Transformers, and encoder-decoder architectures. Familiarity with cloud-native architectures, Kubernetes, and scalable inference platforms (e.g., Triton, vLLM). Preferred Qualifications Experience with open-source LLMs (e.g., LLaMA3, Mistral, Mixtral). Familiarity with retrieval-augmented generation (RAG) architectures and open-source toolkits like Haystack or LangChain. Experience working in a platform team building reusable ML components for wider adoption. Exposure to multi-agent systems, autonomous decision-making, or reinforcement learning is a plus. Understanding of Responsible AI principles including bias detection, explainability, and hallucination mitigation.

Job Description: Total 2 industry experience 3 year experience in applying machine learning techniques to real business problems Key Responsibilities: Managing large machine learning applications and designing and implementing new frameworks to build scalable and efficient data processing workflows and machine learning pipelines Build the tightly integrated pipeline that optimizes and compiles models and then orchestrates their execution Collaborate with CPU GPU and Neural Engine hardware backends to push inference performance and efficiency Work closely with feature teams to facilitate and debug the integration of increasingly sophisticated models including large language models Automate data processing and extraction Engage with sales team to find opportunities understand requirements and translate those requirements into technical solutions Develop reusable ML models and assets into production Technical Requirements: Excellent Python programming and debugging skills Refer to Pytho JD given below Proficiency with SQL relational databases non relational databases Passion for API design and software architecture Strong communication skills and the ability to naturally explain difficult technical topics to everyone from data scientists to engineers to business partners Experience with modern neural network architectures and deep learning libraries Keras TensorFlow PyTorch Experience unsupervised ML algorithms Experience in Timeseries models and Anomaly detection problems Experience with modern large language model Chat GPT BERT and applications Expertise with performance optimization Experience or knowledge in public cloud AWS services S3 Lambda Familiarity with distributed databases such as Snowflake Oracle Experience with containerization and orchestration technologies such as Docker and Kubernetes Preferred Skills: Technology->Machine Learning->Python,Technology->Big Data - Data Processing->Spark,Technology->Machine Learning->R

Mandatory skill :- ML model design, Python, anomaly detection, exp with time series or classification. Cyber Security domain exp is mandatory. statistical techniques and concepts (regression, properties of distributions, statistical tests Required Candidate profile Should be proficient in TensorFlow, PyTorch, Keras and Natural Language Processing (NLP) is essential. share the profile at jayalakshmi@aeliuscityhr.com

Details The ERM manager will play a key role in implementing and overseeing the organizations risk management programme. framework.He/She will be responsible for working with process owners in identifying, assessing and mitigating the risks as well as designing and implementing continuous monitoring of critical risks by the first line of defence. He/She will be responsible for performing independent stress testing and sharing findings with management. The incumbent will work with central team in infusing technology in risk management, defining and implementing system based rules for stress testing. Roles and Responsibilities Collaborate with Functions on risk identification, assessment, and mitigation Helps prepare and execute continuous monitoring of identified risks Develop and implement stress testing frameworks Conduct regular stress testing and identify process gaps and anomalies Prepare and present detailed reports on stress test results to senior management Continually improve the stress testing program to adapt to changing risk landscapes Lead and support on automation/AI initiatives SKill Required Strong knowledge of risk management, stress testing and anomaly detection methodologies Proficient in data analysis Should have good attention for details, good interpersonal, oral, and written communication skills with ability to communicate with all levels of management. Stakeholder Management- Should be able to make presentations to Function heads on risk topics Ability to Recruit and build a high performing team, mentor and motivate team members, manage team performance and ensure necessary training for team members Ability to work in high pressure environments and deliver high quality work Good knowledge of excel, power BI, MS Office Project management Reinvent your world.We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention. Come to Wipro. Realize your ambitions. Applications from people with disabilities are explicitly welcome.

Role/Designation: Data Scientist Location: Gurgaon Level/ Band: Band C (Manager/ Sr. Manager) Brief about the role/ team/ candidate requirement: We are looking for a motivated and highly skilled Data Scientist to join our Flight Safety team. This role will be pivotal in using advanced data analytics and machine learning techniques to enhance flight safety decisions and processes. The candidate will work with time-series, multi-variate data to detect anomalies, identify patterns, and build predictive models that support safety management. The ideal candidate should have a strong foundation in data science, machine learning, and deep learning techniques, along with expertise in applying these skills in the aviation safety domain. The candidate will play a key role in developing algorithms, performing exploratory data analysis, and utilizing artificial intelligence tools to forecast potential safety risks, providing valuable insights for strategic safety decisions. Qualification & Experience: Educational Requirements: Engineering graduate with a specialization in Data Science or a related field. Completion of a Data Scientist course or equivalent certification. Experience: A minimum of 6 years of hands-on experience working directly with data, particularly in the context of data science and machine learning. Skill set: Data analysis Anomaly detection Machine learning Big data analytics Programming skills Job responsibilities: Data analysis expertise: Ability to conduct exploratory data analysis to uncover patterns, trends, and insights from complex datasets. Anomaly detection: Expertise in anomaly detection techniques for time-series, multi-variate data, with a focus on identifying outliers and irregular behavior. Machine learning and deep learning: Strong understanding of data science methodologies, machine learning algorithms, and deep learning architectures such as Artificial Neural Networks (ANN), Recurrent Neural Networks (RNN), and Convolutional Neural Networks (CNN). Big data analytics: Proficient in utilizing AI and machine learning techniques for big data analytics, with the goal of predicting and mitigating potential safety risks. Programming skills: Expertise in Python and MATLAB for data manipulation, modeling, and algorithm development. Algorithm development: Strong ability to formulate custom algorithms tailored to specific requirements, ensuring accurate results in the context of flight safety and operational excellence. Data collection: Proficiency in gathering and preprocessing data from various sources to ensure high-quality datasets for analysis and modeling.

Job Title: Risk Analyst - Commerce Reports To: Lead Fraud Risk Commerce "LOOKING FOR CANDIDATES ONLY FROM E-COMMERCE COMPANIES" About the Role: We are seeking a skilled and detail-oriented Risk Analyst to join our Commerce Risk team. This role is critical in driving risk intelligence through data-backed insights and timely analysis. The ideal candidate will not only work with large datasets and analytical models but will also be responsible for translating technical findings into clear, actionable summaries for leadership and crossfunctional stakeholders. The analyst is expected to identify risks, uncover patterns in user behavior, and support strategic risk mitigation decisions across the platform, particularly in the areas of customer abuse, promotional misuse, and trust violations. Key Responsibilities: Prepare and analyze complex datasets to identify risk patterns, surface anomalies, and validate business hypotheses. Build concise summaries and visualizations that simplify technical data for diverse audiences, enabling informed decision-making across Risk, Product, and Business teams. Communicate insights through clear narratives , providing actionable recommendations and highlighting associated risks and trade-offs . Design and execute BI and reporting frameworks to monitor key metrics, rule performance, and customer impact across commerce brands. Collaborate with data engineering teams to maintain robust data pipelines and models for risk signal generation. Contribute to data modeling efforts and manage risk-centric data structures within the data warehouse. Support development and refinement of risk rules and machine learning models to strengthen detection of fraudulent or abusive behaviors. Maintain documentation and continuously evolve analysis SOPs based on the latest business rules, thresholds, and ecosystem learnings. Role Requirements: Bachelors degree in a quantitative discipline such as Statistics, Mathematics, Economics, Computer Science, or a related field. 3 - 5 years of hands-on experience in risk analytics, fraud detection, or business intelligence , preferably within eCommerce or fintech domains. Proficient in SQL and Python for data extraction, transformation, and visualization; exposure to tools like R, Tableau, Power BI is a plus. Strong understanding of data warehousing, data modeling , and performance monitoring techniques. Experience working with rule-based and predictive risk frameworks is preferred. Excellent communication and storytelling skills, with the ability to present insights to nontechnical audiences in a structured and impactful manner. Proven experience working in cross-functional environments , balancing business priorities and analytical rigor. Basic Qualifications: Bachelor's degree in a quantitative discipline such as Statistics, Mathematics, Economics, Computer Science , or a related field.

AI/ML Architect Experience 10+ years in total, 8+ years in AI/ML development 3+ years in AI/ML architecture Education Bachelors/Masters in CS, AI/ML, Engineering, or similar Title: AI/ML Architect Location: Onsite Bangalore Experience: 10+ years Position Summary: We are seeking an experienced AI/ML Architect to lead the design and deployment of scalable AI solutions. This role requires a strong blend of technical depth, systems thinking, and leadership in machine learning , computer vision , and real-time analytics . You will drive the architecture for edge, on-prem, and cloud-based AI systems, integrating 3rd party data sources, sensor and vision data to enable predictive, prescriptive, and autonomous operations across industrial environments. Key Responsibilities: Architecture & Strategy Define the end-to-end architecture for AI/ML systems including time series forecasting , computer vision , and real-time classification . Design scalable ML pipelines (training, validation, deployment, retraining) using MLOps best practices. Architect hybrid deployment models supporting both cloud and edge inference for low-latency processing. Model Integration Guide the integration of ML models into the IIoT platform for real-time insights, alerting, and decision support. Support model fusion strategies combining disparate data sources, sensor streams with visual data (e.g., object detection + telemetry + 3rd party data ingestion). MLOps & Engineering Define and implement ML lifecycle tooling, including version control, CI/CD, experiment tracking, and drift detection. Ensure compliance, security, and auditability of deployed ML models. Collaboration & Leadership Collaborate with Data Scientists, ML Engineers, DevOps, Platform, and Product teams to align AI efforts with business goals. Mentor engineering and data teams in AI system design, optimization, and deployment strategies. Stay ahead of AI research and industrial best practices; evaluate and recommend emerging technologies (e.g., LLMs, vision transformers, foundation models). Must-Have Qualifications: Bachelors or Master’s degree in Computer Science, AI/ML, Engineering, or a related technical field. 8+ years of experience in AI/ML development, with 3+ years in architecting AI solutions at scale. Deep understanding of ML frameworks (TensorFlow, PyTorch), time series modeling, and computer vision. Proven experience with object detection, facial recognition, intrusion detection , and anomaly detection in video or sensor environments. Experience in MLOps (MLflow, TFX, Kubeflow, SageMaker, etc.) and model deployment on Kubernetes/Docker . Proficiency in edge AI (Jetson, Coral TPU, OpenVINO) and cloud platforms (AWS, Azure, GCP). Nice-to-Have Skills: Knowledge of stream processing (Kafka, Spark Streaming, Flink). Familiarity with OT systems and IIoT protocols (MQTT, OPC-UA). Understanding of regulatory and safety compliance in AI/vision for industrial settings. Experience with charts, dashboards, and integrating AI with front-end systems (e.g., alerts, maps, command center UIs). Role Impact: As AI/ML Architect, you will shape the intelligence layer of our IIoT platform — enabling smarter, safer, and more efficient industrial operations through AI. You will bridge research and real-world impact , ensuring our AI stack is scalable, explainable, and production-grade from day one.

Req ID: 326519 We are currently seeking a Windows Engineering - Systems Engineer to join our team in Bangalore, Karntaka (IN-KA), India (IN). Responsibilities Work with a global team of highly motivated platform engineers and software developers Participate in full platform product lifecycle for windows based solutionsanalysis, technical design, testing, release, and support. Evaluate and test commercial solutions to help drive Buy vs. Build decisions Engineer and maintain automated Windows builds to support desktop on virtualized and cloud environments Execute performance testing of new desktop and server builds on various virtual and physical platforms Basic Qualifications In-depth knowledge in Windows OS internals including Group Policies, Windows Defender, Windows Networking stack, OS build engineering and deployment Experience engineering, managing and supporting environments involving VDI (Citrix, RDS), and Microsoft Desktop and Server platforms (Windows 10, Win11, Server 2016+) Experience in automation, anomaly detection and predictive analysis Experience with Windows Systems Management and Patch management Technologies (SCCM, MECM, Group Policy and WSUS) Extensive experience with one or more scripting technologiesPowerShell, VBS, SQL, Windows Batch Experience with Windows build engineering, particularly experience with SCCM and MDT Experience in supporting secure infrastructure solutions involving DMZ Environment Preferred Qualifications Enterprise-level Financial Services experience is preferred Team player who is able to work in a fast paced, environment Strong verbal and written communication skills Strong analytical and problem solving skills Experience with public cloud environments (AWS Certified Solutions Architect or equivalent) Strong communication skill and able to work with remote counterparts internally and manage external vendors Familiar with Linux, Middleware, Networks, Storage, Email, Mobile Applications, Voice/Video/Multimedia Systems and Market Data Systems