Description: Job Description: Skilled, Tableau along with SQL & .NET with 3-5 Years of Experience, Python Cloud, Kafka, experience with be added advantage, with a focus on data security and handling of PHI and PII. The ideal candidate will have extensive experience with Tableau & .Net and a proven track record of developing secure and compliant data visualizations and reports. The candidate should have excellent data analysis and modeling skills and be comfortable working with large and complex data sets while ensuring data privacy and security. Responsibilities: Develop, design and maintain secure data visualizations and reports using Tableau Work with other teams to integrate Tableau and SQL solutions into larger business intelligence systems while ensuring data privacy and security Participate in the entire software development lifecycle, building, testing and delivering high-quality solutions. Collaborate with cross-functional teams to identify and solve complex problems. Write clean and reusable code that can be easily maintained and scaled. Ensure compliance with data privacy regulations, including handling of PHI and PII Work with stakeholders to understand their data needs and requirements while ensuring data privacy and security Create and manage secure Tableau dashboards for various stakeholders and departments Develop and implement security measures to protect sensitive data Develop SQL scripts and queries to extract, manipulate and analyze large and complex data sets while ensuring data privacy and security Optimize SQL queries for performance and scalability while ensuring data privacy and security Conduct data analysis and modeling to identify trends, patterns, and insights while ensuring data privacy and security Develop, test and maintain high-quality software using Python programming language. Requirements: • Bachelors degree in computer science, Information Technology, or a related field • Strong expertise in Tableau and python • Experience with data visualization and reporting • Strong analytical and problem-solving skills • Experience with data modeling and analysis • Familiarity with database design and optimization • Experience with ETL and data warehousing • Strong understanding of data privacy regulations, including handling of PHI and PII • Strong communication and interpersonal skills • Ability to work independently and as part of a team • Ability to multitask and manage multiple projects simultaneously
Jr. Associate Claims (Business Operations) will be responsible for the following: In this role, required to solve routine problems, largely through precedent and referral to general guidelines Primary interaction is within own team and direct supervisor and will be given detailed instructions on all tasks Read and understand the process documents provided by the customer – Analyze the insurance claims and process as per standard operating procedures Familiarize, navigate multiple client applications and capture necessary information to process insurance claims Consistently meet established productivity, scheduled adherence, and quality standards Adhere to company policies This role may require to work in rotational shifts in office premises as per business requirements
THE POSITION CWP Specialist is accountable for the efficient delivery of CWP PMOs services. This position will work closely with vendors, client hiring managers, and cross-functional teams, utilizing SAP Fieldglass to ensure smooth service delivery. DAY IN THE LIFE A typical day may involve activities such as briefing suppliers, arranging interviews, discussing candidates with hiring managers, conducting pre-employment checks, handling Employee Relations cases, and carrying out induction meetings for new employees. KEY RESPONSIBILITIES Facilitate the fulfillment of temporary requisitions through SAP Fieldglass and efficiently manage the relationship and Assist Hiring managers, Staffing Specialists, and suppliers during all stages of the contract labor acquisition process including but not limited to interview scheduling, onboarding, worker assignment management, time and expense management and off boarding Serve as Single point of contact for Hiring managers, Contingent Workers, and the Suppliers. Proactively meet with hiring managers to qualify requisitions and convey relevant information to approved suppliers to empower them for success Ensure to be inline with agreed SLAs in fulfilling contractor request and onboard contractor by coordinating with different stakeholder Partner closely with key stakeholders (HR OPS, IT OPS, RMG, TA and IT and Legal) to understand global operational needs, identify trends, and develop operational plans that will drive best-in-class evolution of Legatos contingent workforce program. Ensure suppliers have robust understanding of all job requirements Review, add & update new job posting templates and rate card categories when needed Ensure compliance with all contractual requirements as well as company mandated policies and procedures Escalate to the PM any serious issues that requires immediate attention. Document all client reported issues and track resolution through to completion ensuring a high level of customer satisfaction Maintain and update worker assignments to reflect appropriate changes. Provide constant communication to clients, suppliers, contingent workers and other partners. Monitor performance against contract SLA’s (i.e. pending end of assignments, invoicing, time and expense management and vendor compliance tracking) Constant interaction with vendors to ensure new hire paperwork is completed in a timely manner so the contractor can start assignment on time. Additional Knowledge, Skills and Abilities: Strong reporting, report building and analytical skills Solution finder Knowledgeable in foundational data as it relates to VMS software systems (SAP Fieldglass preferred but not required) Good with people and fast paced high volume programs Experience: 5-11 years of VMS Experience on the MSP or supplier side, and / or contingent staffing recruiting WHAT WE ARE LOOKING FOR? A customer-oriented, self-motivated critical thinker with a “Can-Do” attitude! Experience of working in a relevant area such as staffing industry operations, HR/recruiting, MSP or customer service is preferred Strong communication skills with the ability to liaise effectively across all layers of the organization
"4+ years of Full stack experience on Microsoft related technologies. - As a Senior Developer need deep understanding and enterprise level work experience of C#, ASP.NET MVC, .Net Core - Need expertise on SQL Server with respect to Stored Procedures, Query Optimization, Data Modeling, Debugging techniques etc. - Good to have Hands on experience knowledge on AWS, Kubernetes, Docker for deploying and migrating applications. - Exposure to snowflake related to snow SQL and advanced level queries - Expertise knowledge on Bitbucket and project management tools like JIRA. - Advanced JavaScript concepts and hands on experience on Angular or React. - Experience related On-prem and Cloud deployment, debugging of applications. - Required complex problem-solving and analytical skills related to data fetching, data processing and transfer from UI to backend with business logics. - Domain knowledge on Health Care Industry is preferred. - Candidate should be able to independently work on the stories and contribute to the team with defects above and beyond his responsibilities. - Exposure to Build and Deployment tools like Bamboo, Udeploy, Jenkins is and added advantage"
JOB RESPONSIBILITY Primary duties may include but are not limited to: Build data models and dashboards to derive meaningful insights. Performs data mining, analytics, data interpretation and statistical modeling to drive improved workforce outcomes. Develops data mining techniques, reports, statistical methodologies, predictive models, and analytical capabilities using structured and unstructured data. Connects program and process data to performance outcomes, develops advanced dashboards, scorecards, metrics and indices reflective of learning, workforce and business objectives. Trains and promotes use of dashboards and other interactive analytical reporting tools. Consults with Human Resources, Learning & Development and the Business to evaluate needs, formulate the analytics plan, select appropriate data elements and metrics, determines and conducts data sourcing and extraction techniques, identifies and reports data trends, correlations and causations, conducts statistical modeling and analysis, and advises end-users regarding interpretation and best use of information to optimize workforce outcomes to drive individual and organizational performance improvement. Partner with Senior leadership to support People analytics deliverables related to Organization Strategy (e.g., diversity, retention, attrition etc.) Point of contact and subject matter expert for ad hoc people data and analytics requests Identify data capture and analytics efficiency improvements and collaborate with teams to implement Maintain unwavering confidentiality of HR information QUALIFICATION Graduate degree in business analytics, statistics, math, or computer science. EXPERIENCE Overall 8+ years of experience with 2+ years experience in an analytical role under HR related analytics SKILLS AND COMPETENCIES Must Have: • Expert in Reporting tools, SQL, Power platforms and MS Suite. • Analytical skills; hands-on experience in deriving insight from large datasets. Good to Have: Proficiency in Database and Dashboarding tools is a plus
Role & responsibilities Develop and maintain microservice architecture and API management solutions using REST and gRPC for seamless deployment of AI solutions. Design and implement AI pipelines using both predictive modelling and agentic framework. Collaborate with cross-functional teams, including data scientists and product managers, to acquire, process, and manage data for AI/ML model integration and optimization. Design and implement robust, scalable, and enterprise-grade data pipelines to support state-of-the-art AI/ML models. Debug, optimize, and enhance machine learning models, ensuring quality assurance and performance improvements. Familiarity with tools like Terraform, CloudFormation, and Pulumi for efficient infrastructure management. Create and manage CI/CD pipelines using Git-based platforms (e.g., GitHub Actions, Jenkins) to ensure streamlined development workflows. Operate container orchestration platforms like Kubernetes, with advanced configurations and service mesh implementations, for scalable ML workload deployments. Design and build scalable LLM inference architectures, employing GPU memory optimization techniques and model quantization for efficient deployment. Engage in advanced prompt engineering and fine-tuning of large language models (LLMs), focusing on semantic retrieval and chatbot development. Document model architectures, hyperparameter optimization experiments, and validation results using version control and experiment tracking tools like MLflow or DVC. Research and implement cutting-edge LLM optimization techniques, such as quantization and knowledge distillation, ensuring efficient model performance and reduced computational costs. Collaborate closely with stakeholders to develop innovative and effective natural language processing solutions, specializing in text classification, sentiment analysis, and topic modeling. Design and execute rigorous A/B tests for machine learning models, analyzing results to drive strategic improvements and decisions. Stay up-to-date with industry trends and advancements in AI technologies, integrating new methodologies and frameworks to continually enhance the AI engineering function. Contribute to creating specialized AI solutions in healthcare, leveraging domain-specific knowledge for task adaptation and deployment. Skills & Competencies Technical Skills: Advanced proficiency in Python with expertise in data science libraries (NumPy, Pandas, scikit-learn) and deep learning frameworks (PyTorch, TensorFlow) Extensive experience with LLM frameworks (Hugging Face Transformers, LangChain) and prompt engineering techniques Experience with big data processing using Spark for large-scale data analytics Version control and experiment tracking using Git and MLflow Software Engineering & Development: Advanced proficiency in Python, familiarity with Go or Rust, expertise in microservices, test-driven development, and concurrency processing. DevOps & Infrastructure: Experience with Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), and container orchestration (Kubernetes) with Helm and service mesh implementations. LLM Infrastructure & Deployment: Proficiency in LLM serving platforms such as vLLM and FastAPI, model quantization techniques, and vector database management. MLOps & Deployment: Utilization of containerization strategies for ML workloads, experience with model serving tools like TorchServe or TF Serving, and automated model retraining. Cloud & Infrastructure: Strong grasp of advanced cloud services (AWS, GCP, Azure) and network security for ML systems. LLM Project Experience: Expertise in developing chatbots, recommendation systems, translation services, and optimizing LLMs for performance and security. General Skills: Python, SQL, knowledge of machine learning frameworks (Hugging Face, TensorFlow, PyTorch), and experience with cloud platforms like AWS or GCP. Experience in creating LLD for the provided architecture. Experience working in microservices based architecture. Domain Expertise: Strong mathematical foundation in statistics, probability, linear algebra, and optimization Deep understanding of ML and LLM development lifecycle, including fine-tuning and evaluation Expertise in feature engineering, embedding optimization, and dimensionality reduction Advanced knowledge of A/B testing, experimental design, and statistical hypothesis testing Experience with RAG systems, vector databases, and semantic search implementation Proficiency in LLM optimization techniques including quantization and knowledge distillation Understanding of MLOps practices for model deployment and monitoring Professional Competencies: Strong analytical thinking with ability to solve complex ML challenges Excellent communication skills for presenting technical findings to diverse audiences Experience translating business requirements into data science solutions Project management skills for coordinating ML experiments and deployments Strong collaboration abilities for working with cross-functional teams Dedication to staying current with latest ML research and best practice Ability to mentor and share knowledge with team members