10 Anova Jobs

Role & responsibilities Collect, clean, and validate data from multiple sources to ensure quality and accuracy. Design and implement statistical models and methodologies to solve real-world problems. Analyze trends, patterns, and relationships in complex data sets. Develop and apply predictive and inferential models. Communicate findings through reports, visualizations, and presentations. Collaborate with cross-functional teams, including data scientists, researchers, business analysts, and management. Stay current with developments in statistical methodologies, software tools, and best practices. Provide guidance on experimental design and data collection strategies. Ensure compliance with data governance, privacy laws, and industry regulations. Preferred candidate profile Masters degree in Statistics, Mathematics, Data Science, or a related field (PhD preferred for advanced research roles). Proven experience in statistical analysis, modeling, and experimental design. Proficiency in statistical software such as R, SAS, Python, or SPSS. Strong knowledge of probability theory, hypothesis testing, regression, and multivariate analysis. Experience with data visualization tools (e.g., Tableau, Power BI, ggplot2, matplotlib). Excellent problem-solving, communication, and organizational skills. Ability to translate complex statistical concepts into actionable business insights.

Role & responsibilities Collect, clean, and validate data from multiple sources to ensure quality and accuracy. Design and implement statistical models and methodologies to solve real-world problems. Analyze trends, patterns, and relationships in complex data sets. Develop and apply predictive and inferential models. Communicate findings through reports, visualizations, and presentations. Collaborate with cross-functional teams, including data scientists, researchers, business analysts, and management. Stay current with developments in statistical methodologies, software tools, and best practices. Provide guidance on experimental design and data collection strategies. Ensure compliance with data governance, privacy laws, and industry regulations. Preferred candidate profile Masters degree in Statistics, Mathematics, Data Science, or a related field (PhD preferred for advanced research roles). Proven experience in statistical analysis, modeling, and experimental design. Proficiency in statistical software such as R, SAS, Python, or SPSS. Strong knowledge of probability theory, hypothesis testing, regression, and multivariate analysis. Experience with data visualization tools (e.g., Tableau, Power BI, ggplot2, matplotlib). Excellent problem-solving, communication, and organizational skills. Ability to translate complex statistical concepts into actionable business insights.

Job Summary: We are looking for a Data Scientist to lead data-driven solutions across our business, from exploratory analysis, incremental hypothesis validation, model development, deployment and monitoring. This role involves transforming complex business questions into actionable value generation insights and predictive models. Key Responsibilities: Problem Definition: Partner with stakeholders to translate business goals into clear, data-focused questions and define project scope and success metrics. Data Collection and Preparation: Gather, clean, and preprocess data from diverse sources, ensuring quality and consistency, and engineer features to enhance model performance. Exploratory Data Analysis (EDA): Use statistical methods and visualization to uncover trends and validate assumptions, summarizing key insights for business alignment. Model Building and Evaluation: Select, train, and refine models suited to the business problem, evaluating performance with relevant metrics and documenting model assumptions. Deployment and Monitoring: Work with engineering teams to deploy models, establish performance monitoring, retrain as necessary, and incorporate feedback to improve accuracy. Requirements: Bachelor s/Master s in Data Science, Statistics, Computer Science, or related field. Experience in end to end model development to deployment and performance monitoring. Strong communication skills to convey insights to technical and non-technical audiences. Skills Needed: Strong knowledge of Applied AI ML & Deep Learning Data Science techniques, Hardcore in ANN /Deep Learning /Machine Learning/NLP Deep knowledge about machine learning algorithms such as tree-based methods, clustering, regression and classification, dimension reduction techniques, linear regression, Logistic regression, k-means, time series forecasting, Hypothesis testing (ANOVA, t-test, etc.), random forest, SVMs, Naive Bayes, gradient boosting, kNN, Deep learning algorithms like CNN, ANN and Reinforcement learning, Anomaly detection. In-depth understanding of Statistical concepts e.g. Probability distributions, statistical tests, correlation analysis, descriptive statistics, kernels, ROC, F1-Score etc. Advanced coding experience in at least one programming language (Python, Pyspark) & Strong experience in object-oriented concepts. Good to have advanced experience in one or more of the following: Spark, Databricks, Azure technical stack Good to have experience in model deployment to cloud/on-prem. Good Communication & presentation skills.

Why Join Us? To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win. We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees passion for travel and ensure a rewarding career journey. We re building a more open world. Join us. This role is part of the Home team within the Product Analytics and Experimentation organization. The team supports the Product team by providing insights and incrementally measurement to help inform decisions on product features. Our team is looking for an established performer who consistently applies analytical capabilities, principles, and playbooks to solve business problems, with moderate guidance and direction. The role involves regular interaction with stakeholders up to the Senior Manager level. In this role, you will: Extract and integrate data from multiple sources to support model building and analytics. Design and recommend both simple and complex experiments (e.g., A/B, pre/post, causal impact) to address business questions. Build basic models (e.g., linear, logistic, clustering) and select appropriate data structures and formats. Develop and maintain basic data pipelines and workflows that support modeling tasks. Work with stakeholders in an iterative, collaborative process to refine project scope and requirements. Apply business knowledge to shape modeling questions, select features, and guide decisions. Deliver clear and concise data stories and visualizations that support decision-making. Automate recurring reporting and dashboarding tasks across multiple platforms (web, app, geo). Share documentation, code, and project artifacts (e.g., executive summaries, tech docs, visualizations) with relevant audiences. Communicate project goals, methods, caveats, and insights to both technical and non-technical stakeholders. Collaborate openly with analytics peers through brainstorming, peer review, and knowledge sharing. Train and enable stakeholders to use dashboards and self-service tools; promote data literacy. Troubleshoot and resolve data issues and ensure efficient query and pipeline performance. Uphold best practices for code sharing and documentation using tools like GitHub, IEX, and Confluence. Continuously seek feedback and apply it to improve current and future projects. Experience and qualifications: Experience 1-2 years of experience in a data analytics role for Bachelor s/Master s graduates (preferably in Mathematics or a scientific discipline), or 2+ years in a comparable professional setting. Proven track record of delivering data-driven insights and recommendations that led to business impact or performance improvements. Technical Skills Intermediate proficiency in R , Python , or SQL for analyzing, structuring, and visualizing large datasets. Competent in extracting, transforming, and combining data from multiple sources. Able to build basic models (e.g., linear/logistic regression, clustering) and support them with appropriate data formats. Experienced in writing efficient, reusable code and creating basic data pipelines. Familiarity with tools like GitHub, IEX, and Confluence for code sharing and documentation. Working knowledge of query optimization and data quality best practices. Statistical & Analytical Knowledge Basic understanding of probability, descriptive statistics (e.g., ANOVA, regression), and frequentist concepts. Ability to design and interpret experiments (e.g., A/B, pre/post, causal impact). Capable of framing business problems as analytical tasks and selecting suitable methodologies. Business & Domain Knowledge Strong business acumen with the ability to align analytics to strategic objectives. Understanding of key data sources, their business context, and appropriate use in modeling. Ability to identify relevant features and guide model design decisions. Communication & Collaboration Strong communication and influencing skills, with experience tailoring insights to both technical and non-technical audiences. Skilled in creating clear, audience-appropriate data visualizations, with awareness of inclusive design principles. Collaborative team player open to feedback, peer review, and knowledge sharing. Mindset & Problem Solving Demonstrated critical thinking and curiosity with a proactive, solutions-focused approach. Comfortable working iteratively and independently, adjusting based on feedback and findings. Strong skills in information gathering, problem solving, and continuous learning. Accommodation requests If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request . We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others. Expedia Groups family of brands includes: Brand Expedia , Hotels.com , Expedia Partner Solutions, Vrbo , trivago , Orbitz , Travelocity , Hotwire , Wotif , ebookers , CheapTickets , Expedia Group Media Solutions, Expedia Local Expert , CarRentals.com , and Expedia Cruises . 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. . Never provide sensitive, personal information to someone unless you re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs . Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.

A Day in the Life As a member of GO SC group you will collaborate closely with all the necessary stakeholders on the assigned tasks and projects including your counterparts in the US to ensure timely and successful completion of the same The Prin. Manufacturing Engineer will closely collaborate with cross-functional project teams within MEIC and GOUs. This role involves leading medium to high complexity supplier transfers and optimization projects, focusing on vertical integrations, cost optimizations and supply chain management. The incumbent will be instrumental in fostering business engagements, enhancing value through process improvements, and adopting best practices. A Day in the Life Be a part of the Medtronic Engineering and Innovation center (MEIC) by applying your skills to the growth and development of Supplier Optimization team under Global supply mangement group team within MEIC. As a member of GO SC group you will collaborate closely with all the necessary stakeholders on the assigned tasks and projects including your counterparts in the US to ensure timely and successful completion of the same The Prin. Manufacturing Engineer will closely collaborate with cross-functional project teams within MEIC and GOUs. This role involves leading medium to high complexity supplier transfers and optimization projects, focusing on vertical integrations, cost optimizations and supply chain management. The incumbent will be instrumental in fostering business engagements, enhancing value through process improvements, and adopting best practices. Validation Processes: Conduct Operational Qualification (OQ) and Performance Qualification (PQ) processes. Assist in developing Master Validation Plans, including process flow, OQ, and PQ. Statistical Analysis: Perform CPK (Process Capability Index) and ANOVA (Analysis of Variance) studies. Conduct criticality analysis to ensure process reliability and quality. Measurement System Analysis (MSA): Perform GRR (Gage Repeatability and Reproducibility) studies. Identify and implement appropriate types of MSA. Risk Management: Conduct PFMEA (Process Failure Mode and Effects Analysis) and calculate Risk Priority Numbers (RPN). Documentation: Develop and maintain work instructions, ensuring they are clear and comprehensive Must-Have: Minimum of 15 years of relevant experience. Minitab software Hands-on experience in manufacturing Engineering projects Familiarity with Regulated manufacturing environment Excellent interpersonal, influence management, and conflict resolution skills. Strong written, verbal, and presentation skills. Effective planning and organization skills, including the ability to work against multiple objectives simultaneously. Bachelor of Engineering in Mechanical or related (Electircal, electronics) Engineering field. Nice to Have: Project management skills with a track record of managing projects to schedule, budget, and scope. Masters degree Manufacturing process knowledge GDT Certification Benefits Compensation About Medtronic We lead global healthcare technology and boldly attack the most challenging health problems facing humanity by searching out and finding solutions. Our Mission to alleviate pain, restore health, and extend life unites a global team of 95,000+ passionate people. We are engineers at heart putting ambitious ideas to work to generate real solutions for real people. From the RD lab, to the factory floor, to the conference room, every one of us experiments, creates, builds, improves and solves. We have the talent, diverse perspectives, and guts to engineer the extraordinary. Learn more about our business, mission, and our commitment to diversity here

This role, GOSO(Global Operations Strategy Organization) - Sales Force Optimization Associate Consultant/Sr. Associate consultant, will report to the GOSO SFO US Manager and work within a team set up to provide critical capabilities for US Affiliate. These capabilities may include, Customer Segmentation & Targeting , Sales force Sizing, Structure, Territory Alignment Design and Maintenance, Field Call planning and Refinement, Dynamic Targeting, Reporting etc. Key accountabilities will include the following: Collate information regarding the field force size, structure, performance, etc. for purposes of analysis Conduct analysis of the data and cascade the overall sales target to the sales associate level Create models such as the customer behaviour profile to support the sales teams to enhance and track performance of the field force against plans Use data and reports to develop, optimize, and implement strategies aimed at improving sales teams performance Develop approaches to design and align territories, incl. structure, size, and deployment Leverage statistical analyses such as regression, Anova, A/B testing etc. to track KPIs, draw insights & suggest course correction, if required. Use datasets such as field execution, tool activity, sales, surveys etc. to track & tweak the deployed field engagement platforms Provide inputs to optimize the field force effectiveness through processes such as Sales Force Sizing, Alignment Design, Personnel Placement, Targeting, Incentives etc. Create models such as the customer behaviour profile to support the sales teams to enhance and track performance of the field force against plans. Setup recurring Tableau, Power BI reports to measure key KPIs of field force execution Use data and reports to develop, optimize, and implement strategies aimed at improving sales teams performance Automate excel-based operations to SQL/Python for improving processing turn-around time, and set-up quality assurance procedures Present insights & results to key stakeholders for driving key business decisions Manage projects independently by performing tasks such as project planning & scoping, delegation, results read-out & feedback assimilation Basic Qualifications: Bachelor s Degree Ensure compliance with company policies and any applicable state and federal marketing and promotion laws and regulations Additional Skills/Preferences: BTech/ MBA with 4-6 years of experience in sales planning and management Knowledge of data analytics and visualization tools (BI, Tableau), Javelin suite of products, CRM systems, Veeva, SQL, AWS, and MS Office Excellent communication (written & verbal) and prioritization skills with attention to detail Strong learning agility Strong analytical mindset High level of motivation and a strong desire to find creative solutions to challenging situations Keen focus on detail, accuracy, and ability to solve problems, supported by strong analytical reasoning Experience in business analysis

Relevant 6-8 years having Electromechanical Background. Strong experience in creating and managing documentation, such as Good Documentation Practices (GDP), in regulated industries like medical devices, pharmaceuticals, and aerospace. Proficient in statistical tools such as Minitab, with experience in techniques like ANOVA, t-tests (1t, 2t), Gage R&R, DOE (Design of Experiments), Monte Carlo simulations, and understanding statistical concepts like resolution. Solid understanding of translating Design Master Records (DMR) into production processes, with knowledge of both R&D and manufacturing activities (similar to roles like an industrialization engineer at Philips). Proven ability to communicate clearly and collaborate with global stakeholders, and effectively manage multiple manufacturing activities across teams. Experience performing and guiding product validation tests (such as TMV, IQ, OQ, and PQ) directly on the shop floor. Ideally, a background in verification or validation within regulated industries.

Job Description Have you ever thought about what it takes to detect and prevent fraudulent activity among hundreds of millions of e-commerce transactions across the globe? What would you do to increase trust in an online marketplace where millions of buyers and sellers transact? How would you build systems that evolve over time to proactively identify and neutralize new and emerging fraud threats? Our mission in Payment Risk is to make Amazon the safest place to transact online. Payment Risk safeguards every financial transaction across all Amazon sites, while striving to ensure that these efforts are transparent to our legitimate customers. As such, Payment Risk designs and builds the software systems, risk models and operational processes that minimize risk and maximize trust in Amazon. com. As a Business Analyst in Payment Risk Analytics, you will be responsible for analyzing terabytes of data to identify specific instances of risk, broader risk trends and points of customer friction, developing scalable solutions for prevention. You will work with team members to ensure that the volume being flagged for manual review aligns with available capacity and Service Level Agreements (SLA s) are met. You will be responsible for building a robust set of operational and business metrics and will utilize metrics to determine improvement opportunities. Responsibilities: Understand the various operations across Payment Risk Design and develop highly available dashboards and metrics using SQL and Excel/Tableau Understand the requirements of stakeholders and map them with the data sources/data warehouse Own the delivery and backup of periodic metrics, dashboards to the leadership team Draw inferences and conclusions, and create dashboards and visualizations of processed data, identify trends, anomalies Execute high priority (i. e. cross functional, high impact) projects to improve operations performance with the help of Operations Analytics managers Perform business analysis and data queries using appropriate tools Work closely with internal stakeholders such as business teams, engineering teams, and partner teams and align them with respect to your focus area Execute analytical projects and understanding of analytical methods (like ANOVA, Distribution theory, regression, forecasting, Machine Learning Techniques, etc. ) Key job responsibilities Understand the various operations across Payment Risk Design and develop highly available dashboards and metrics using SQL and Excel/Tableau Understand the requirements of stakeholders and map them with the data sources/data warehouse Own the delivery and backup of periodic metrics, dashboards to the leadership team Draw inferences and conclusions, and create dashboards and visualizations of processed data, identify trends, anomalies Execute high priority (i. e. cross functional, high impact) projects to improve operations performance with the help of Operations Analytics managers Perform business analysis and data queries using appropriate tools Work closely with internal stakeholders such as business teams, engineering teams, and partner teams and align them with respect to your focus area Execute analytical projects and understanding of analytical methods (like ANOVA, Distribution theory, regression, forecasting, Machine Learning Techniques, etc. ) - 1+ years of tax, finance or a related analytical field experience - 2+ years of complex Excel VBA macros writing experience - Bachelors degree or equivalent - Experience defining requirements and using data and metrics to draw business insights - Experience with SQL or ETL - Experience with reporting and Data Visualization tools such as Quick Sight / Tableau / Power BI or other BI packages

ql-editor "> Job Summary We are seeking a skilled In Vitro Statistician with 2-7 years of experience to support our research and development teams in statistical analysis of in vitro studies. The ideal candidate will be responsible for designing experiments, analyzing data, and providing statistical insights to support decision-making in pharmaceutical, biotechnology, or life sciences research. Key Responsibilities: Design, develop, and analyze in vitro study experiments, ensuring statistical rigor and accuracy. Apply appropriate statistical models and methodologies for data interpretation. Work closely with scientists, biologists, and researchers to provide statistical guidance in study design and result evaluation. Utilize statistical software (e.g., SAS, R, JMP, or Python) to conduct data analysis, visualization, and reporting. Validate and verify data integrity, ensuring compliance with regulatory guidelines (FDA, ICH, GLP). Develop and review statistical analysis plans (SAPs), study protocols, and technical reports. Support regulatory submissions by preparing statistical documentation and reports. Stay updated with the latest statistical methods and best practices in in vitro research. Required Qualifications Skills: Master s or Ph.D. in Statistics, Biostatistics, Bioinformatics, or a related field. 2-7 years of experience in statistical analysis of in vitro studies, preferably in the pharmaceutical, biotechnology, or life sciences sector. Strong knowledge of experimental design, regression models, ANOVA, DOE, and multivariate analysis. Proficiency in statistical software (SAS, R, JMP, Python, or equivalent). Experience with data visualization, trend analysis, and predictive modeling. Understanding of regulatory requirements and compliance standards (FDA, ICH, GLP). Excellent communication skills to present findings to cross-functional teams. Strong problem-solving skills and attention to detail. Preferred Qualifications: Experience in bioassays, pharmacokinetics, biomarker analysis, or toxicology studies. Familiarity with machine learning and AI-based statistical modeling. Knowledge of clinical and preclinical statistical applications.

Have you ever thought about what it takes to detect and prevent fraudulent activity among hundreds of millions of e-commerce transactions across the globe? What would you do to increase trust in an online marketplace where millions of buyers and sellers transact? How would you build systems that evolve over time to proactively identify and neutralize new and emerging fraud threats? Our mission in Buyer Risk Prevention is to make Amazon the safest place to transact online. Buyer Risk Prevention safeguards every financial transaction across all Amazon sites, while striving to ensure that these efforts are transparent to our legitimate customers. As such, Buyer Risk Prevention designs and builds the software systems, risk models and operational processes that minimize risk and maximize trust in Amazon. com. As a Business Analyst in Buyer Risk Prevention, you will be responsible for analyzing terabytes of data to identify specific instances of risk, broader risk trends and points of customer friction, developing scalable solutions for prevention. You will need to collaborate effectively with business and product leaders within BRP and cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. You should be able to apply a breadth of tools, data sources, and analytical techniques to answer a wide range of high-impact business questions and proactively present new insights in concise and effective manner. In addition you will be responsible for building a robust set of operational and business metrics and will utilize metrics to determine improvement opportunities. You should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business. Responsibilities: - Understand the various operations across Payment Risk - Design and develop highly available dashboards and metrics using SQL and Excel/Tableau - Perform business analysis and data queries using scripting languages like R, Python etc - Understand the requirements of stakeholders and map them with the data sources/data warehouse - Own the delivery and backup of periodic metrics, dashboards to the leadership team - Draw inferences and conclusions, and create dashboards and visualizations of processed data, identify trends, anomalies - Execute high priority (i. e. cross functional, high impact) projects to create robust, scalable analytics solutions and frameworks with the help of Analytics/BIE managers - Perform business analysis and data queries using appropriate tools - Work closely with internal stakeholders such as business teams, engineering teams, and partner teams and align them with respect to your focus area - Execute analytical projects and understanding of analytical methods (like ANOVA, Distribution theory, regression, forecasting, Machine Learning Techniques, etc. ) - Draw inferences and insights from the data using EDA and data manipulations using advanced SQL for business reviews Key job responsibilities Understand the various operations across Payment Risk Design and develop highly available dashboards and metrics using SQL and Excel/Tableau/QuickSight Understand the requirements of stakeholders and map them with the data sources/data warehouse Own the delivery and backup of periodic metrics, dashboards to the leadership team Draw inferences and conclusions, and create dashboards and visualizations of processed data, identify trends, anomalies Execute high priority (i. e. cross functional, high impact) projects to improve operations performance with the help of Analytics managers Perform business analysis and data queries using appropriate tools Work closely with internal stakeholders such as business teams, engineering teams, and partner teams and align them with respect to your focus area Execute analytical projects and understanding of analytical methods (like ANOVA, Distribution theory, regression, forecasting, Machine Learning Techniques, etc. ) - Bachelors degree in finance, accounting, business, economics, engineering , analytics, mathematics, statistics or a related technical or quantitative field - 3+ years of business analyst, data analyst or similar role experience - 5+ years of Excel (including VBA, pivot tables, array functions, power pivots, etc. ) and data visualization tools such as Tableau experience - Experience defining requirements and using data and metrics to draw business insights - Experience with Excel - Experience with SQL - Experience making business recommendations and influencing stakeholders - Experience with data visualization using Tableau, Quicksight, or similar tools - Experience creating complex SQL queries joining multiple datasets, ETL DW concepts - Experience demonstrating problem solving and root cause analysis - Experience using databases with a large-scale data set - Detail-oriented and must have an aptitude for solving unstructured problems. The role will require the ability to extract data from various sources and to design/construct/execute complex analyses to finally come up with data/reports that help solve the business problem