14 Anomaly Detection Jobs

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

Senior Data Scientist Location: Onsite Bangalore Experience: 8+ years Role Overview We are seeking a Senior Data Scientist with a strong foundation in machine learning, deep learning, and statistical modeling, with the ability to translate complex operational problems into scalable AI/ML solutions. In addition to core data science responsibilities, the role involves building production-ready backends in Python and contributing to end-to-end model lifecycle management. Exposure to computer vision is a plus, especially for industrial use cases like identification, intrusion detection, and anomaly detection. Key Responsibilities Develop, validate, and deploy machine learning and deep learning models for forecasting, classification, anomaly detection, and operational optimization Build backend APIs using Python (FastAPI, Flask) to serve ML/DL models in production environments Apply advanced computer vision models (e.g., YOLO, Faster R-CNN) to object detection, intrusion detection, and visual monitoring tasks Translate business problems into analytical frameworks and data science solutions Work with data engineering and DevOps teams to operationalize and monitor models at scale Collaborate with product, domain experts, and engineering teams to iterate on solution design Contribute to technical documentation, model explainability, and reproducibility practices Required Skills Strong proficiency in Python for data science and backend development Experience with ML/DL libraries such as scikit-learn, TensorFlow, or PyTorch Solid knowledge of time-series modeling, forecasting techniques, and anomaly detection Experience building and deploying APIs for model serving (FastAPI, Flask) Familiarity with real-time data pipelines using Kafka, Spark, or similar tools Strong understanding of model validation, feature engineering, and performance tuning Ability to work with SQL and NoSQL databases, and large-scale datasets Good communication skills and stakeholder engagement experience Good to Have Experience with ML model deployment tools (MLflow, Docker, Airflow) Understanding of MLOps and continuous model delivery practices Background in aviation, logistics, manufacturing, or other industrial domains Familiarity with edge deployment and optimization of vision models Qualifications Masters or PhD in Data Science, Computer Science, Applied Mathematics, or related field 7+ years of experience in machine learning and data science, including end-to-end deployment of models in production

Job Summary: We are looking for an experienced SAS Visual Investigator (SAS VI) Developer to support our fraud detection, risk management, and compliance initiatives. The ideal candidate will leverage SAS VI to analyze large datasets, identify suspicious patterns, generate alerts, and build visual interfaces for real-time investigation. This role is critical in enhancing our enterprise fraud management capabilities and delivering actionable insights to business and compliance teams. Key Responsibilities: Design, develop, and implement solutions using SAS Visual Investigator for fraud detection, risk management, and anomaly detection. Analyze large and complex datasets to investigate suspicious activities and uncover potential fraudulent behavior. Build and maintain dynamic dashboards, visualizations, and alerts within SAS VI to support real-time decision-making. Integrate SAS VI with other systems, ensuring seamless data flow and operational effectiveness. Collaborate with compliance, IT, and analytics teams to support investigative workflows and reporting needs. Ensure high data quality, integrity, and security through rigorous validation and testing. Continuously monitor, evaluate, and enhance detection models and SAS VI configurations to improve performance. Stay current with evolving industry trends, fraud typologies, and regulatory standards in fraud risk and compliance. Qualifications: Proven hands-on experience with SAS Visual Investigator (SAS VI), preferably in a fraud or risk context. Strong understanding of fraud detection methodologies and compliance practices. Proficiency in data analysis, pattern recognition, and anomaly detection using SAS tools. Experience in developing and maintaining interactive dashboards and alert systems. Ability to work with large datasets and conduct detailed forensic data analysis. Knowledge of the SAS ecosystem including SAS Visual Analytics, SAS Data Integration, or SAS Viya, is a plus. Strong communication and documentation skills with the ability to translate findings for non-technical stakeholders. Experience integrating SAS VI with external systems and APIs is advantageous.

About Zscaler Serving thousands of enterprise customers around the world including 40% of Fortune 500 companies, Zscaler (NASDAQ: ZS) was founded in 2007 with a mission to make the cloud a safe place to do business and a more enjoyable experience for enterprise users. As the operator of the world’s largest security cloud, Zscaler accelerates digital transformation so enterprises can be more agile, efficient, resilient, and secure. The pioneering, AI-powered Zscaler Zero Trust Exchange™ platform, which is found in our SASE and SSE offerings, protects thousands of enterprise customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Named a Best Workplace in Technology by Fortune and others, Zscaler fosters an inclusive and supportive culture that is home to some of the brightest minds in the industry. If you thrive in an environment that is fast-paced and collaborative, and you are passionate about building and innovating for the greater good, come make your next move with Zscaler. Our Engineering team built the world's largest cloud security platform from the ground up, and we keep building. With more than 100 patents and big plans for enhancing services and increasing our global footprint, the team has made us and our multitenant architecture today's cloud security leader, with more than 15 million users in 185 countries. Bring your vision and passion to our team of cloud architects, software engineers, security experts, and more who are enabling organizations worldwide to harness speed and agility with a cloud-first strategy. We're looking for an experienced Staff Software Engineer to join our Unified API platform team. Reporting to the Director, you'll be responsible for: Leading identification and resolution of performance issues by developing advanced AI/ML models that pinpoint root causes of poor experience and detect performance bottlenecks for users Developing, maintaining, and refining predictive models to forecast user behavior, system performance, and potential friction points in the digital experience Implementing advanced AI/ML algorithms to detect and forecast anomalies in user experience across multiple dimensions Overseeing the entire lifecycle of ML projects, including analysis, training, testing, building, and deploying ML models into production environments Designing and creating compelling visualizations to effectively communicate findings and insights to both technical and non-technical stakeholders What We're Looking for (Minimum Qualifications) A Bachelors or Master’s(preferable) degree in Computer Science, Data Science, Statistics, or a related field with 4+ years of professional experience in data science or a related role Proficiency with data science tools and platforms such as Python, R, TensorFlow, SQL, and related libraries and frameworks Strong experience with networking and end-point observability systems Expertise in multi-dimensional anomaly detection algorithms, with a specific focus on time series data sets Strong experience in building and deploying ML models in production environments, including model orchestration using tools like Kubernetes and Airflow What Will Make You Stand Out (Preferred Qualifications) Published research or contributions to digital experience/end-user observability/networking/ data science community Demonstrated experience in the monitoring space, with a deep understanding of user experience metrics, monitoring tools, and methodologies Experience with designing complex systems and scaling ML models on large scale distributed systems #LI-Hybrid #LI-AN4 At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure. Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including: Various health plans Time off plans for vacation and sick time Parental leave options Retirement options Education reimbursement In-office perks, and more! By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines. Zscaler is committed to providing equal employment opportunities to all individuals. We strive to create a workplace where employees are treated with respect and have the chance to succeed. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status, or any other characteristic protected by federal, state, or local laws. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link. Pay Transparency Zscaler complies with all applicable federal, state, and local pay transparency rules. Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.

Job Summary: We are seeking a skilled professional with experience in SAS Visual Investigator (SAS VI) to help enhance our fraud detection and risk management initiatives In this role, you will work with advanced SAS tools to analyze complex data, detect anomalies, and investigate suspicious activities Your key responsibilities will include identifying patterns, generating alerts for potential fraud risks, and developing visualizations and dashboards to present insights to stakeholders You will also play a vital role in ensuring compliance and contributing to the continuous improvement of fraud prevention strategies. Key Responsibilities: Design and implement solutions in SAS VI for fraud detection, risk management, compliance, and anomaly detection. Investigate suspicious activities by analyzing large datasets to identify patterns and fraud risks. Develop and maintain dashboards and visualizations to communicate insights and alerts to stakeholders. Use SAS VI to detect and alert fraudulent activities, ensuring compliance and timely intervention. Collaborate with teams to integrate SAS VI with other systems for seamless fraud management. Continuously assess and improve fraud detection processes and system performance. Ensure data quality and integrity with rigorous validation and troubleshooting in SAS VI. Stay updated on trends and best practices in fraud detection, compliance, and anomaly detection. Qualifications: Use SAS VI for fraud detection, risk management, and anomaly detection. Investigate suspicious activities, identify patterns, and generate alerts. Develop dashboards and visualizations to present findings. Integrate SAS VI with other systems for fraud management. Ensure data quality and improve fraud detection processes Bachelors degree in Computer Science, Data Analytics, Statistics, or a related field.

About Firstsource Firstsource Solutions is a leading provider of customized Business Process Management (BPM) services. Firstsource specialises in helping customers stay ahead of the curve through transformational solutions to reimagine business processes and deliver increased efficiency, deeper insights, and superior outcomes. We are trusted brand custodians and long-term partners to 100+ leading brands with presence in the US, UK, Philippines, India and Mexico. Our rightshore delivery model offers solutions covering complete customer lifecycle across Healthcare, Telecommunications & Media and Banking, Financial Services & Insurance verticals. Our clientele includes Fortune 500 and FTSE 100 companies. Fraud Technical Specialist Band 4 What You Will Do: Reporting into the Fraud Technical Lead, you will work as part of a team to help underpin the delivery of Skys Technical Fraud strategy ensuring Sky is afforded the highest level of protection via efficient and optimal use of best-in-class fraud controls. Undertake operational tasks that ensure the smooth running of Skys fraud function across multiple systems. Continually build comprehensive knowledge of common fraud trends through a mixture of analyst feedback and proactive interrogation of data. Present rule configuration changes to the Fraud Technical Lead with the aim of optimising overall fraud detection. Respond to information requests by developing customised reports through the combination of SQL database queries and ad-hoc data extracts. Be able to go beyond figures and deliver meaningful insight in a way that can be easily digested by various stakeholders to help answer the important questions. Be involved in maintaining quality assurance of fraud systems through user acceptance testing of upgrade deployments and or system enhancements. Ensure functional deliveries match expected requirements whilst all bugs and issues are removed prior to production release. Respond to system incidents by working with relevant support teams / vendors to resolve operational issues within the defined schedules and service level agreements. Apply commercial judgement to correctly prioritize operational malfunctions and ensure impactful system issues are appropriately escalated. Key Skills & Experience Include: Highly numerate preferably with experience in a data analysis role Strong proven SQL experience is a must Solid critical thinking and methodical approach when dealing with technical issues Demonstrates resilience when faced with competing priorities Previous fraud experience advantageous but not essential Disclaimer: Firstsource follows a fair, transparent, and merit-based hiring process. We never ask for money at any stage. Beware of fraudulent offers and always verify through our official channels or @firstsource.com email addresses.

Role & responsibilities: Design and implement transaction monitoring rules and models for merchant financing and payments. Analyze merchant transaction data to detect suspicious, fraudulent, or anomalous behavior patterns. Collaborate with data science teams to build and refine anomaly detection algorithms using machine learning and statistical methods. Perform deep dives on flagged transactions to identify root causes and patterns. Work closely with risk, product, compliance, and engineering teams to define detection strategies and enhance risk scoring systems. Maintain and improve the transaction monitoring system, including rule tuning and false positive reduction. Ensure timely escalation and reporting of suspicious activity to compliance and regulatory bodies as required (e.g., SARs/STRs). Conduct post-incident analysis to improve detection capabilities and reduce future risk. Prepare periodic reports and dashboards for senior management and regulatory reporting. Preferred candidate profile : Required Qualifications Bachelors or master’s degree in finance, Data Science, Statistics, Computer Science, or related field. 7+ years of experience in transaction monitoring, fraud analytics, or anomaly detection in financial services, preferably in merchant/acquirer finance. Strong analytical skills with hands-on experience in SQL, Python or other analytical tools. Experience with rule-based and machine learning-based anomaly detection systems. Familiarity with merchant behavior analytics, risk profiling, and fraud typologies. Understanding of AML (Anti-Money Laundering), KYC, and regulatory requirements. Excellent communication and documentation skills.

Description BS/MS degree in Computer Science or equivalent 1015 years of experience building products on distributed systems, preferably in the Data Security domain Working knowledge of the security domain - Ransomware protection, Anomaly detection, data classification and compliance of unstructured data. Strong knowledge of Cloud platform, APIs, containers, Kubernetes, and Snowflake Knowledge of building micro-service-based applications. Hands-on development in either Golang or Python Strong development experience in Linux/Unix OS platform

About Zscaler Serving thousands of enterprise customers around the world including 40% of Fortune 500 companies, Zscaler (NASDAQ: ZS) was founded in 2007 with a mission to make the cloud a safe place to do business and a more enjoyable experience for enterprise users. As the operator of the world’s largest security cloud, Zscaler accelerates digital transformation so enterprises can be more agile, efficient, resilient, and secure. The pioneering, AI-powered Zscaler Zero Trust Exchange™ platform, which is found in our SASE and SSE offerings, protects thousands of enterprise customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Named a Best Workplace in Technology by Fortune and others, Zscaler fosters an inclusive and supportive culture that is home to some of the brightest minds in the industry. If you thrive in an environment that is fast-paced and collaborative, and you are passionate about building and innovating for the greater good, come make your next move with Zscaler. Our Engineering team built the world's largest cloud security platform from the ground up, and we keep building. With more than 100 patents and big plans for enhancing services and increasing our global footprint, the team has made us and our multitenant architecture today's cloud security leader, with more than 15 million users in 185 countries. Bring your vision and passion to our team of cloud architects, software engineers, security experts, and more who are enabling organizations worldwide to harness speed and agility with a cloud-first strategy. We're looking for an experienced Machine Learning Software Development Engineer to join our Engineering team. Reporting to the Senior Director, Machine Learning Engineering, you'll be responsible for: Leading the identification and resolution of performance issues by developing models that pinpoint root causes of poor experience and detect performance bottlenecks Developing, maintaining, and refining predictive models to forecast user behavior, system performance, and potential friction points Implementing AI/ML algorithms to detect and forecast anomalies in user performance data across multiple dimensions Overseeing the entire lifecycle of ML projects, including analysis, training, testing, building, and deploying ML models into production environments Designing and creating compelling visualizations to effectively communicate findings and insights to both technical and non-technical stakeholders What We're Looking for (Minimum Qualifications) Must have 3+ years of experience as a Software Engineer or ML platform engineer Proficiency with data science tools and platforms such as Python, R, TensorFlow, SQL, and related libraries and frameworks 7+ years of experience in Python and SQL Expertise in multi-dimensional anomaly detection algorithms, with a specific focus on time series data sets Experience in building and deploying ML models in production environments, including model orchestration using tools like Kubernetes and Airflow What Will Make You Stand Out (Preferred Qualifications) Network troubleshooting using tools like traceroute and understanding of various protocols such as HTTP, TCP, ICMP is highly advantageous Familiarity with Generative AI and NLP techniques Familiarity with networking and systems observability #LI-AN4 #LI-Hybrid At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure. Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including: Various health plans Time off plans for vacation and sick time Parental leave options Retirement options Education reimbursement In-office perks, and more! By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines. Zscaler is committed to providing equal employment opportunities to all individuals. We strive to create a workplace where employees are treated with respect and have the chance to succeed. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status, or any other characteristic protected by federal, state, or local laws. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link. Pay Transparency Zscaler complies with all applicable federal, state, and local pay transparency rules. Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.

# Contact +91 9947189235 (Share CV in Whatsapp) # Credentials- 1) For Hospitals, Medical Colleges and Diagnostic centres 2) Locations: South IND/ Kerala 3) Salary: 3L to 5 L per month (respective of Exp & Location) 4) Qualification: DNB/MD/DMRD Perks and benefits Accomodation Available

Looking for a strong ML engineer with end to end exposure in ML lifecycle , Azure etc Strong background in data science and machine learning, particularly in anomaly detection. Experience in deploying ML models to production in cloud environments.