263 Hypothesis Testing Jobs

Role Overview: Expedia Group is looking for an experienced analytics professional to join the AI Agent Product Analytics Team. In this mid-level individual contributor role, you will partner with product managers to focus on user experience optimization through GenAI-driven personalization. As a Data Scientist, you will collaborate with a diverse team to apply quantitative analysis, machine learning, and data visualization to solve business problems and drive product development. Your role will involve uncovering customer friction points, hypothesis generation, experiment design, test analysis, and product optimization to improve the user experience for millions of Expedia customers. Key Responsibilities: - Apply expertise in quantitative analysis, machine learning, data mining, and data visualization to enhance customer experience and business outcomes - Provide actionable insights to guide product teams - Lead end-to-end testing excellence, including evaluating A/B and multivariate tests, identifying opportunities, and recommending new features for test-and-learn initiatives - Evaluate and implement alternative methods to support randomized testing - Develop metrics frameworks, build user-friendly dashboards/reports, and collaborate on goal setting, performance reviews, and strategic planning - Proactively identify and recommend optimal solutions for current and potential problems based on trade-offs Qualifications Required: - 4+ years of experience in quantitative analysis for solving business problems - Bachelor's degree in a science, technology, engineering, or mathematics (STEM) field - Strong analytical skills with the ability to dissect complex business scenarios - Proficiency in SQL or programming languages such as R or Python, and experience with large datasets - Excellent communication skills to convey compelling stories using data - Solid understanding of statistics and hypothesis testing, including confidence intervals, regression, time series, clustering, and factor analysis - Familiarity with visualization tools like Tableau, and experience with Adobe Analytics or Google Analytics is a plus - Detail-oriented with a strong curiosity and passion for making an impact If you are a self-starter who has demonstrated success in driving innovation and user engagement through analytics, this role at Expedia Group is tailored for you. Join us in shaping the future of travel and be part of our diverse and welcoming community where everyone's contribution is valued.,

Lead Data Scientist - Neoware Technology Solutions Private Limited Lead Data Scientist Requirements 8 12 years of experience in Data Science/AI, with at least 3 4 years leading ML/GenAI solution delivery Strong foundation in Python, ML/AI frameworks, cloud platforms (AWS, Azure, GCP), and LLM-based architectures with vector databases and RAG pipelines Strong understanding of BI tools, actionable insights, hypothesis testing, business recommendations Proven track record of taking solutions from design deployment adoption Experience in estimating infra requirements and cost of ownership Education: Degree in Statistics, Mathematics, Economics, Computer Science, AI/ML, Data Science, or any equivalent quantitative field A go-getter, ambitious yet practical leader with excellent problem-solving, communication, and stakeholder management skills Responsibilities Blueprint & Architecture: Translate business needs into logical workflows, data flows, and technical architectures Solution Delivery: Build and deploy GenAI capabilities (document intelligence, semantic search, summarization, conversational Q&A) and ML solutions (Linear and non-linear forecasting, classification, clustering, recommendation engines, anomaly detection, model accuracy, explainability, traceability etc.) Deployment & Ops: Implement MLOps/GenAIOps practices CI/CD, monitoring, retraining, and governance Cost & Ownership: Prepare Bill of Materials, infra sizing, and cost of ownership models for client and internal deployments Team Leadership: Mentor and guide data scientists/engineers to deliver high-quality, production-ready solutions Stakeholder Engagement: Communicate solutions clearly, align with client priorities, and drive adoption

Data scientists at Thoughtworks are responsible for leading and executing data science projects. They employ their profound expertise in statistics, modeling, machine learning algorithms and data mining methodologies. They integrate this expertise with a comprehensive understanding of related domains to render business value and illuminate data-driven insights, facilitating clear and effective decision-making processes. Their responsibilities encompass devising strategies, executing plans, operationalizing solutions and articulating the tangible business outcomes achieved. Collaborating with cross-functional teams is pivotal, as they adeptly convey their discoveries to both technical and non-technical stakeholders. They stay up-to-date with industry advancements, ensure data quality and security, and provide guidance to junior team members. As a data scientist at Thoughtworks, you'll work on a range of projects and leverage deep technical knowledge to solve complex business problems. Job responsibilities You will lead and manage data science projects from inception to completion, including goal-setting, scope definition and ensuring on-time delivery with cross team collaboration. You will collaborate with stakeholders to understand their strategic objectives and identify opportunities to leverage data and data quality for enabling AI and machine learning. You will be responsible for the overall AI system design, problem framing and governance, identifying and managing risks and issues. You will design, develop and implement data science strategies that drive measurable business results. You will design experiments for the team to rapidly test ideas and assumptions, and identify future courses of action. You will use quality metrics to select machine learning models that will be deployed in the production environment. You will communicate technical findings and insights to stakeholders in a clear, easy and concise way, keeping the stakeholders in mind. You will contribute to the growth of the data science community along with promoting a culture of data literacy within the organization. You will address ethical concerns and adhere to ethical guidelines using FATTER AI (fairness, accountability, transparency, trustworthiness, explainability, responsibility). You will work with CD4ML practices and data versioning tools. Job qualifications Technical Skills You have experience in leading the analysis and modeling of different datasets and overseeing an inception to deploying and productionizing the models. You have experience with statistical modeling, hypothesis testing, machine learning, deep learning, optimization and other data science techniques to implement end-to-end data science projects. You understand the specialized areas of AI and possess a speciality with at least one of them (i.e.: NLP/computer vision/Generative AI, etc)tc). You have experience with R, Python or equivalent statistical/data analysis tools and can write production-ready code that is easy to evolve and test. You gather and preprocess large volumes of structured and unstructured data from various sources, ensuring data quality and integrity. You analyze datasets using statistical and visualization techniques to identify patterns, trends and relationships. You develop and implement machine learning models, algorithms and predictive analytics to solve specific business problems or improve existing processes. You evaluate model performance using appropriate metrics and validate models to ensure robustness and reliability. You interpret and effectively communicate findings and insights to non-technical stakeholders through reports, presentations and visualizations. You ensure compliance with data privacy regulations and ethical standards when handling sensitive information. Professional Skills You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way. You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives. You dont shy away from risks or conflicts, instead you take them on and skillfully manage them. You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work. You enjoy influencing others and always advocate for technical excellence while being open to change when needed. You are a proven leader with a track record of encouraging teammates in their professional development and relationships. Cultivating strong partnerships comes naturally to you; You understand the importance of relationship building and how it can bring new opportunities to our business.

The Analytics Centre of Excellence (ACOE) at Airbnb, based in India, is a hub of knowledge and expertise that aims to provide data-driven decision-making, enabling Airbnb's business goals. The ACOE's vision is to build a world-class analytics organization that provides scalable analytics. We work with various business functions such as payments, trust, digital, customer support, hosting, sales, social, compliance, risk, platforms and partnership & economics. The ACOE's delivery framework is designed to provide relevant and contextual insights for data-driven decisions. This includes a one-stop solution for metrics, dashboards driving actionable insights, optimization of performance, measuring pre/post feature impact, sizing the ROI of opportunities, prioritization of opportunities, anomaly-driven alerting mechanisms, root cause analysis of metric deviation, and exploratory hypothesis testing. The Community You Will Join: We are looking for a hands-on Staff, Advanced Analytics who has demonstrated success in building an analytics team with functional expertise in building analytical solutions. Be a trusted partner to product teams and business leaders, across marketplace teams through providing insights, recommendations, and enabling data driven decisions. This role will sit under the Advanced Analytics family and support Product and Business leaders within our CS organization. The Difference You Will Make: Data thought partner to product and business leaders across marketplace teams through providing insights, recommendations, and enabling data informed decisions. Drive day to day product analytics and build analytical solutions Develop a deep understanding of how guests and hosts interact with our CS products including but not limited to AI Assistant, IVR and other agent assisting tools to improve the customer experience. A Typical Day: Owning the product analytics road map, prioritization & delivery of solutions in the Contact Center Product space. Own projects from start to end: building out timelines, key milestones, providing regular updates to product managers, analytics management and delivery against agreed timelines. Lead end-to-end measurement for AI systems, aligning metrics with business outcomes, user experience, and trustworthiness Collaborate with engineering to define scale logging and ensure observability across Agentic and LLM workflows. Lead the design and evaluate A/B and causal tests to quantify impact of AI features and optimizations. Translate insights into strategic recommendations for senior leaders; shape product priorities through data. Hire, mentor and up level team capability in AI analytics, experiment best practices and storytelling. Your Expertise: 12+ years in industry experience and a degree (Masters or PhD is a plus) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research). Expert communication and collaboration skills with the ability to work effectively with internal teams in a cross-cultural and cross-functional environment. Ability to conduct rigorous analysis and communicate conclusions to both technical and non-technical audiences Strong expertise in Python, SQL, A/B testing platforms and best practices Expertise in EDA, hypothesis testing, significance testing, regression, clustering techniques, concepts of NLP/Text Mining, machine learning and deep learning techniques, language model fine-tuning etc Understanding of LLM architectures (e.g., prompt chains, retrieval augmentation, orchestration frameworks like LangChain or DSPy). Familiarity with Agentic AI systems, human-in-the-loop design, and AI observability best practices Experience partnering with internal teams to drive action and providing expertise and direction on analytics, data science, experimental design, and measurement. Experience designing and building metrics, from conception to building prototypes with data pipelines Familiarity with vector stores, embeddings, prompt instrumentation, and structured logging of LLM interactions would be a plus Contact center domain and market place domain knowledge would be a plus Our Commitment To Inclusion & Belonging : Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We seek trainers/teacher in Data Engineering/Science, Cloud Computing &DevOps(JaipurPreferred) . Role starts part-time, can be done with your current job. Industrial experience preferred; no prior teaching experience required. High earning potentia l.

Role Overview: As a Quant Analyst, AVP at Deutsche Bank in Mumbai, India, you will be part of the Strategic Analytics team, which plays a central role in the bank's Investment Bank, Corporate Bank, and Risk and Control functions. Your primary responsibility will be to develop a scalable Front Office pricing and risk management system to ensure consistency in analytics and technology platform across different bank units. Key Responsibilities: - Collaborate with teams in London, New York, and Frankfurt on quantitative and regulatory projects - Understand business problems, gather necessary information, and provide optimized solutions on a scalable platform - Implement projects using Python and C++ programming languages - Communicate effectively with stakeholders globally - Develop complex processes, risk analysis frameworks, and enhancements - Measure market risks across the bank and design automated, scalable solutions - Coordinate with stakeholders to understand business requirements and design databases - Develop applications and libraries for solution implementation - Remediate regulatory and internal findings related to risk models - Ensure quality assurance through reviews Qualification Required: - At least 4 years of experience in Python/C++ programming - Strong knowledge of OOPs concepts, data structures, and pulling data from market sources - Ability to independently address weaknesses identified by regulators and auditors - Excellent communication and presentation skills - Strong problem-solving and analytical skills - Educational background in Engineering/Science, Economics, Statistics, or related fields from reputable institutions (e.g., IIT, NIT, ISI) - Knowledge of financial instruments, pricing models, and risk models - Experience with applied econometrics and certification courses like CFA/FRM/CQ would be a plus Additional Details: Deutsche Bank promotes a culture of continuous learning, offers training and development opportunities, coaching from experts, and a range of flexible benefits to support your career growth. The company values responsibility, commercial thinking, initiative, and collaboration to excel together every day. For more information about Deutsche Bank and its teams, please visit their website: [Deutsche Bank Website](https://www.db.com/company/company.htm),

This position is part of the Analytical Solutions team that executes custom analysis and data delivery projects for comScore’s external clients and supports certain internal data feeds. This team is located within comScore’s product organization and is focused mainly on transforming comScore’s national and local television usage data into custom data feeds for clients. In this role, the Data Scientist will utilize their skills and knowledge in statistics and media research, working closely with other members of the Analytical Solutions and CMS Custom Analytics teams, and with internal and external clients, to develop and maintain value-added solutions. What You'll Do: Effectively handle large data files in the course of developing and implementing solutions Precisely execute multiple analytic projects, each involving a great number of steps and analytic decisions Concisely summarize real-world implications of findings from custom projects and the value proposition of real-world offerings Interpret results, present findings and recommend alternative solutions to software and business decision makers Translate statistical modeling results into measures of business impact Interface with clients to aid in the qualification of custom analytical solutions Manage expectations and coordinate project delivery with internal team Play a key role in the development and adaptation of statistical methodologies, including traditional media research methodologies, for the development, maintenance and improvement of data products Develop statistical tools to facilitate and improve data regression, manipulation, and analysis Test and measure the effectiveness of new statistical approaches and process improvements Assist Custom Solutions team in new product development. Execute prototyping of new product ideas Manage analytic projects What You'll Need: 2- 4 years related experience in traditional, direct, or digital media research; understand traditional (TV) media math and targeting concepts Ph.D. or Masters (M.S.) in Statistics, Decision Sciences, Economics, Physics, Systems Engineering, or Mathematics preferred Highly competent in quantitative and qualitative analysis, regression, data manipulation, and critical thinking. Intrinsic ability to look at data and identify patterns, problems, or analysis opportunities Ability to distill large amounts of information into key findings Excellent written, verbal, and presentation skills and an ability to explain complex systems Extensive background in data mining applications, including proven programming and debugging ability in SAS, R, Python or similar language. Experience analyzing person-level or household-level marketing data and efficiently handling large data files Extensive experience with relational DB data access including writing and debugging SQL Proficient in navigating and scripting on *NIX systems Experience with wide range of market research methodologies within and beyond media measurement: regression, time series, SEM, marketing mix, Bayesian methods Experience with experimental design, hypothesis testing, power calculations for statistical tests About Comscore: At Comscore, we’re pioneering the future of cross-platform media measurement, arming organizations with the insights they need to make decisions with confidence. Central to this aim are our people who work together to simplify the complex on behalf of our clients & partners. Though our roles and skills are varied, we’re united by our commitment to five underlying values: Integrity, Velocity, Accountability, Teamwork, and Servant Leadership. If you’re motivated by big challenges and interested in helping some of the largest and most important media properties and brands navigate the future of media, we’d love to hear from you. Comscore (NASDAQ: SCOR) is a trusted partner for planning, transacting and evaluating media across platforms. With a data footprint that combines digital, linear TV, over-the-top and theatrical viewership intelligence with advanced audience insights, Comscore allows media buyers and sellers to quantify their multiscreen behavior and make business decisions with confidence. A proven leader in measuring digital and set-top box audiences and advertising at scale, Comscore is the industry’s emerging, third-party source for reliable and comprehensive cross-platform measurement. To learn more about Comscore, please visit Comscore.com. C omscore is committed to creating an inclusive culture, encouraging diversity. *LI-JL1

Data scientists at Thoughtworks are responsible for leading and executing data science projects. They employ their profound expertise in statistics, modeling, machine learning algorithms and data mining methodologies. They integrate this expertise with a comprehensive understanding of related domains to render business value and illuminate data-driven insights, facilitating clear and effective decision-making processes. Their responsibilities encompass devising strategies, executing plans, operationalizing solutions and articulating the tangible business outcomes achieved. Collaborating with cross-functional teams is pivotal, as they adeptly convey their discoveries to both technical and non-technical stakeholders. They stay up-to-date with industry advancements, ensure data quality and security, and provide guidance to junior team members. As a data scientist at Thoughtworks, you'll work on a range of projects and leverage deep technical knowledge to solve complex business problems. Job responsibilities You will lead and manage data science projects from inception to completion, including goal-setting, scope definition and ensuring on-time delivery with cross team collaboration. You will collaborate with stakeholders to understand their strategic objectives and identify opportunities to leverage data and data quality for enabling AI and machine learning. You will be responsible for the overall AI system design, problem framing and governance, identifying and managing risks and issues. You will design, develop and implement data science strategies that drive measurable business results. You will design experiments for the team to rapidly test ideas and assumptions, and identify future courses of action. You will use quality metrics to select machine learning models that will be deployed in the production environment. You will communicate technical findings and insights to stakeholders in a clear, easy and concise way, keeping the stakeholders in mind. You will contribute to the growth of the data science community along with promoting a culture of data literacy within the organization. You will address ethical concerns and adhere to ethical guidelines using FATTER AI (fairness, accountability, transparency, trustworthiness, explainability, responsibility). You will work with CD4ML practices and data versioning tools. Job qualifications Technical Skills You have experience in leading the analysis and modeling of different datasets and overseeing an inception to deploying and productionizing the models. You have experience with statistical modeling, hypothesis testing, machine learning, deep learning, optimization and other data science techniques to implement end-to-end data science projects. You understand the specialized areas of AI and possess a speciality with at least one of them (i.e.: NLP/computer vision/Generative AI, etc)tc). You have experience with R, Python or equivalent statistical/data analysis tools and can write production-ready code that is easy to evolve and test. You gather and preprocess large volumes of structured and unstructured data from various sources, ensuring data quality and integrity. You analyze datasets using statistical and visualization techniques to identify patterns, trends and relationships. You develop and implement machine learning models, algorithms and predictive analytics to solve specific business problems or improve existing processes. You evaluate model performance using appropriate metrics and validate models to ensure robustness and reliability. You interpret and effectively communicate findings and insights to non-technical stakeholders through reports, presentations and visualizations. You ensure compliance with data privacy regulations and ethical standards when handling sensitive information. Professional Skills You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way. You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives. You dont shy away from risks or conflicts, instead you take them on and skillfully manage them. You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work. You enjoy influencing others and always advocate for technical excellence while being open to change when needed. You are a proven leader with a track record of encouraging teammates in their professional development and relationships. Cultivating strong partnerships comes naturally to you; You understand the importance of relationship building and how it can bring new opportunities to our business.

Role Overview: As an Analyst at Lowe's Pricing Analytics team, your primary role will involve developing and maintaining descriptive and predictive analytics models and tools to support Lowe's pricing strategy. You will collaborate closely with the Pricing team to translate pricing goals into data and analytics requirements. Utilizing open source and commercial data science tools, you will gather and analyze data to provide data-driven insights, trends, and identify anomalies. Your expertise in statistical and machine learning techniques will be crucial in answering relevant questions and providing retail recommendations for the company to achieve its targets. Key Responsibilities: - Translate pricing strategy and business objectives into analytics requirements. - Develop processes for collecting, exploring, structuring, and cleaning large datasets from internal and external sources. - Validate data, detect outliers, and perform root cause analysis to prepare data for statistical and machine learning models. - Research, design, and implement statistical and machine learning models to solve business problems. - Ensure accuracy and reliability of model results and apply them to relevant business use cases. - Educate the pricing team on interpreting and utilizing machine learning model results effectively. - Design and execute A/B tests, multivariate experiments, and randomized controlled trials to evaluate the effects of price changes. - Conduct advanced statistical analyses to extract actionable insights from experimentation data. - Lead and manage analytics projects, ensuring they are completed on time and aligned with business objectives. - Explore and implement new analytical techniques, tools, and industry best practices. - Collaborate with cross-functional teams to define, prioritize, and develop innovative solutions. - Keep up to date with developments in data science, machine learning, statistics, and experimentation techniques. - Mentor junior analysts to foster skill development and growth within the team. Qualifications Required: - Bachelor's or Master's degree in Engineering, Business Analytics, Data Science, Statistics, Economics, or Mathematics. - 6-12 years of relevant experience in advanced quantitative analysis, statistical modeling, and machine learning models. Additional Details: At Lowe's India, you will be part of a team that supports the $97 billion home improvement business through technology, analytics, business operations, finance & accounting, product management, and shared services. The company leverages new technologies and innovative methods to maintain a competitive edge in the market.,

As an experienced consulting professional in the field of Data Science or AI/ML Engineering, you will be responsible for understanding solutions, industry best practices, and implementing Oracle products and technology to meet customer needs. You will operate independently to deliver high-quality work products to engagements, applying Oracle methodology, company procedures, and leading practices. **Key Responsibilities:** - Lead end-to-end AI/ML solution design and production deployment - Specialize in Generative AI, LLMs, NLP, and AI agent development - Expertise in Python and modern ML/NLP frameworks such as HuggingFace, LangChain, PyTorch, TensorFlow - Fine-tune LLMs for domain-specific applications like Q&A systems, auto-documentation, and predictive insights - Build, scale, and optimize AI systems on OCI with knowledge of hybrid/multi-cloud architectures - Strong knowledge of machine learning algorithms, prompt engineering, vector databases, and RAG pipelines - Familiarity with MLOps, model governance, and CI/CD for ML workflows - Excellent communication and stakeholder management skills to bridge the gap between technical and executive teams **Qualifications & Experience:** - 12-15 years of total experience, with a minimum of 5 years in Data Science or AI/ML Engineering roles - Proven track record in AI/ML solution design and deployment - Expertise in Python and modern ML/NLP frameworks - Hands-on experience with AI systems on OCI and knowledge of multi-cloud architectures - Strong knowledge of machine learning algorithms, prompt engineering, and model governance - Experience in stakeholder engagement, program oversight, and solution design **Additional Details:** The company is committed to an inclusive culture that celebrates diverse insights and perspectives, fostering an environment that inspires thought leadership and innovation. Oracle offers a competitive suite of Employee Benefits designed on the principles of parity, consistency, and affordability, including Medical, Life Insurance, Retirement Planning, and more. The company encourages employees to engage in giving back to communities and values diversity and inclusion in the workforce. If you are looking for a challenging role where you can leverage your expertise in AI/ML engineering to drive innovative solutions and work in a diverse and inclusive environment, this position at Oracle might be the perfect fit for you.,

Your Role Gen AI ,Computer vision, Cloud exp , Azure Need to understand how the products are developed and even more important, as big data touches the privacy of consumers, they need to have a set of ethical Need to have a natural desire to go beneath the surface of a problem. Confident and self-secure as they more often than not will have to deal with situations where there is a lot of unknown. Good knowledge & experience in Artificial Neural Network ( ANN ), AI conversational Chatbot & Needs to be able to write the required Algorithm and coding programming. Preferably in different programming languages such as Python, Tensor Flow, Keras, AWS (ML and DL), Numpy, and Pytorch. Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications.1. Applies scientific methods to analyse and solve software engineering problems.2. He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance.3. His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers.4. The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities.5. The software engineer collaborates and acts as team player with other software engineers and stakeholders. Your Profile Natural Language Processing, Machine learning, Conceptual modeling, Statistical analysis, Predictive Modeling, and Hypothesis testing. Data scientists should have at least some of the following capabilities Cleaning data, formatting data, Having the ability to query databases & perform statistical analysis, building AI Data Modelling, validating the AI Model, and deployment. Being able to develop or program databases. Having a good understanding of design & architecture principles. What will you love working at Capgemini Every Monday, kick off the week with a musical performance by our in-house band - The Rubber Band. Also get to participate in internal sports events , yoga challenges, or marathons. At Capgemini, you can work on cutting-edge projects in tech and engineering with industry leaders or create solutions to overcome societal and environmental challenges. Employees rate thework culture highly (4.1/5), appreciating the collaborative environment and supportive teams Hybrid work modelsandflexible timingsare common, with many roles offering remote or partially remote options

Work Flexibility: Hybrid Who we want: Detail-oriented process improvers. Critical thinkers who naturally see opportunities to develop and optimize work processes finding ways to simplify, standardize and automate. Self-directed imitators. People who take ownership of their work and need no prompting to drive productivity, change, and outcomes. Analytical problem solvers. People who go beyond just fixing to identify root causes, evaluate optimal solutions, and recommend comprehensive upgrades to prevent future issues. Goal-oriented developers. Keeping the customer and requirements squarely in focus, people who deliver safe and robust solutions. Delivers results. A driven player who sets high goals for personal achievement and organizational success. He/she measures success against the best internal and external benchmarks What you will do The Clinical Evaluation Specialistacts as the lead technical expert in driving this highly complex and demanding process. He/she applies scientific, regulatory and project management skills toestablish the evaluationstrategy andtocompile the body of Clinical Evidence, allowing, in collaboration with the Medical Expert, toreach a legally binding scientific conclusion on the safety and performance ofdevicesin patients, throughout the product lifecycle.The Clinical Evaluation Specialist bears the operational and regulatory responsibility ofindividual clinical evaluation reportsand may defend them in audit situations.Tasks include- Driving the establishment of a coherent Clinical Evidence strategy throughout the new product development cycle and fostering alignment with adjacent complex processes (Marketing strategy and claims, regulatory strategy, clinical research strategy, testing strategy). Designingcompliant and sustainable literature search strategies, and performingcomplex literature queries toretrievepublished clinical data, Identifying, appraising,and analyzingall relevant (clinical, PMS, marketing, and testing data) from multiple sources and formats and create a comprehensive scientific review, including in depth statistical analyses, risk management cross-check and descriptive analyses, following complex and rigorous methodologies. Analyzingthe current medical and scientific trends in the clinical State of the Art on a broad variety of specialized indications and techniques. Based on a detailed and up-to-date understanding of US, European and Australian regulatoryrequirements,and expectations, elaborate, and defend, with the Medical Expert, a conclusion on the overall risk-benefit statement. Identify unanswered questions and residual risks in the Clinical Evidence, and design Post Market Clinical Follow Up activities in collaboration with Clinical Research to address these questions. Defining anddevelopingClinicalEvaluation and analysis methodologies to adapt to a complex and quickly evolving regulatory and scientific framework. SupportingMarketing in the creation and review of collateral and promotional material to ensure alignment of messaging and claims to regulatory compliance, scientific accuracy, and clinical evidence. With the Medical Experts, helpingto define, plan, and initiate clinical studies and in vitro tests together with all stakeholders from Clinical Research, R&D, Biomechanics and Regulatory. What you need: Education: University degree (PhD, Masters or equivalent) in a field related to the life sciences or a relevant medical engineeringfield (biology, physiology, biomaterials, biomedical engineering or similar). Experience: 3to5years of experience in Scientific or Medical Writing, and/orrelevantacademicor clinicalresearch experience (PhD, Post-doc) Experience in clinical or regulatory affairs preferred Experience withorthopedic or trauma devices preferred Proactive, independent, team player with a strong service mentality. You arecharacterized by analytical and transdisciplinary reasoning, with a good attention to detail. You value an international working environment, working across sites and indications.Travel Percentage: 10%

Role Overview: As a Senior Manager Product Tooling & Data (Data Focused) in the Group Investment Management (GIM) Team at London Stock Exchange Group (LSEG), your primary responsibility will be to interpret and utilize data science and analytics to support the team in predicting and managing programme execution risks. Your role will involve developing machine learning models and early warning indicators to identify and mitigate delivery risks across a multi-million-pound change portfolio. By transforming complex programme data into predictive insights, you will drive strategic investment decisions and contribute to fostering a culture of delivery excellence and transparency within the organization. Key Responsibilities: - Lead the design and implementation of machine learning models to predict programme delivery risks and financial overruns. - Integrate insights into existing dashboards and visualizations to effectively communicate with senior leadership and ensure actionable and trackable risk metrics. - Collaborate with senior stakeholders to understand data needs and translate them into technical solutions. - Conduct data cleaning, preprocessing, and integration from multiple sources, including internal databases and APIs. - Contribute to the development of Group-wide delivery framework and assurance standards. - Stay updated with advancements in AI/ML and apply them to enhance risk prediction and decision-making. - Support the annual investment planning process through data-driven analysis and scenario planning. Qualifications Required: - Proficiency in Python or R, with experience in libraries such as scikit-learn, TensorFlow, or similar. - Experience in LLM prompt engineering for feature extraction from unstructured data. - Strong SQL and data wrangling skills, including experience with ETL processes. - Solid understanding of statistical analysis and hypothesis testing. - Experience in building and deploying machine learning models in a business context. - Ability to communicate technical insights to non-technical audiences using visualization tools like Tableau and matplotlib. - Familiarity with fine-tuning small LLM models for automating topic extraction from unstructured data. - Knowledge of cloud platforms, especially AWS Bedrock and Snowflake data platform. - Experience with enterprise programme management tools like Clarity, Asana, and JIRA. - Familiarity with SAP ERP and Workday systems data. - Experience in financial services or programme delivery environments. - Strong communication and collaboration skills. - Self-starter with the ability to manage multiple priorities in a fast-paced environment. - Commitment to continuous learning and innovation. [Note: Additional details about the company's values and purpose have been omitted from the Job Description as they are not directly related to the role.] ,

Role Overview: You will be working as a Spec Analytics Analyst (C11) in the TTS Analytics team at Citi. Your main responsibilities will include working on various analyses throughout the year to solve business problems related to client acquisition, engagement, client experience, and retention within the TTS business. You will be involved in data science and business analytics projects, developing machine learning models, and communicating insights and recommendations to stakeholders. Key Responsibilities: - Work on multiple analyses throughout the year on business problems across the client life cycle including acquisition, engagement, client experience, and retention for the TTS business - Design, develop, and deploy machine learning models to address business needs - Communicate insights and recommendations to stakeholders - Leverage various analytical approaches, tools, and techniques to provide data-driven insights and machine learning solutions Qualifications Required: - Bachelor's or Master's Degree with 5-8 years of experience in data science and analytics - Marketing analytics experience - Experience in sales/marketing strategy optimization, pricing optimization, client experience, cross-sell, and retention - Strong understanding of machine learning principles, model development methodologies, and deployment strategies - Hands-on knowledge of Data Science and Machine Learning, including supervised and unsupervised learning algorithms - Experience with time series models, unstructured data analysis using NLP/Text Mining techniques, and building machine learning pipelines - Proficient in PySpark, SQL (Python/R), Scikit-learn, TensorFlow, PyTorch, MS Excel, PowerPoint - Good to have experience with Tableau and Hive Company Details (if present): The TTS Analytics team at Citi provides analytical insights to various functions within the global Treasury & Trade Services business. They focus on driving acquisitions, cross-sell, revenue growth, and improvements in client experience by extracting relevant insights, identifying business opportunities, building predictive models, and designing go-to-market strategies for different business problems.,

In this role of Digital Analytics Analyst, you are expected to have a good knowledge of the range of processes, procedures, and systems related to the assigned tasks, along with a basic understanding of the underlying concepts and principles. You should have a good understanding of how your team interacts with others to achieve objectives. Your responsibilities will involve making evaluative judgments based on factual information, resolving problems by identifying and selecting solutions through your technical experience, and being able to exchange information concisely while being sensitive to audience diversity. Your impact on the business will be limited to your own job tasks and services provided. Key Responsibilities: - Statistical analysis and hypothesis testing - Assisting with solutions and implementations - Performing relatively complex and varied assignments - Demonstrating technical and administrative expertise - Applying specialized functional area skills and basic knowledge - Having a basic knowledge of the organization and its policies - Appropriately assessing risk in business decisions, with a focus on compliance and ethical judgment Qualifications Required: - 1.5 - 4 years of relevant experience in Digital Analytics - Experience working with Adobe - Experience working with data leveraging SQL or Python - Strong communication skills Please note that this job description gives an overview of the work involved, and additional job-related duties may be assigned as necessary. If you are a person with a disability and require a reasonable accommodation to use the search tools or apply for a career opportunity, please review Accessibility at Citi. You can also view Citis EEO Policy Statement and the Know Your Rights poster for more information.,

Role Overview: You will be a data scientist responsible for developing and deploying impactful data solutions using your expertise in machine learning and statistical analysis. Your role will involve designing and implementing predictive models, collaborating with stakeholders, and driving strategic decisions through experimentation and data-driven insights. Key Responsibilities: - Design and implement robust machine learning solutions including regression, classification, NLP, time series, and recommendation systems. - Evaluate and tune models using appropriate metrics like AUC, RMSE, precision/recall, etc. - Work on feature engineering, model interpretability, and performance optimization. - Partner with stakeholders to identify key opportunities where data science can drive business value. - Translate business problems into data science projects with clearly defined deliverables and success metrics. - Provide actionable recommendations based on data analysis and model outputs. - Conduct deep-dive exploratory analysis to uncover trends and insights. - Apply statistical methods to test hypotheses, forecast trends, and measure campaign effectiveness. - Design and analyze A/B tests and other experiments to support product and marketing decisions. - Automate data pipelines and dashboards for ongoing monitoring of model and business performance. Qualification Required: - Proficiency in Python and MySQL. - Experience with libraries/frameworks such as scikit-learn, Pandas, NumPy, Time series, ARIMA, Bayesian model, Market Mix model, Regression, XGBoost, LightGBM, TensorFlow, PyTorch. - Proficient in statistical techniques like hypothesis testing, regression analysis, and time-series analysis. - Familiarity with databases like PostgreSQL, BigQuery, and MySQL. - Knowledge of visualization tools like Plotly, Seaborn, and Matplotlib. - Experience in Gitlab, CI/CD pipelines is a plus. - Familiarity with cloud platforms like AWS, GCP, or Azure services is also advantageous. In case of any additional details of the company, they are not provided in the job description.,

You are invited to join Chryselys, a Pharma Analytics & Business consulting company based in Hyderabad with a hybrid work setup. Our focus is on delivering data-driven insights through AI-powered, cloud-native platforms to drive high-impact transformations. At Chryselys, we excel in digital technologies and advanced data science techniques that offer strategic and operational insights. Our team comprises industry veterans, advisors, and senior strategists with diverse backgrounds from top-tier companies. We prioritize delivering the value of a big five consulting firm without the associated costs. Our solutions are business-centric and built on cloud-native technologies. As a Data Scientist at Chryselys, your responsibilities will include designing, developing, and implementing machine learning models and algorithms to analyze pharmaceutical datasets, leveraging platforms such as IQVIA, Symphony, Veeva, and Open data. You will use advanced statistical techniques and data science methodologies to extract insights from complex data sources. Building and maintaining data pipelines and scalable machine learning models on Data Lake architecture using cloud-based platforms like AWS (Redshift, S3, SageMaker) is also part of your role. Collaboration with cross-functional teams to translate business problems into data science solutions is essential. You will be expected to create and present data visualizations, dashboards, and reports using tools like PowerBI, Tableau, Qlik, QuickSight, and ThoughtSpot to effectively communicate findings and recommendations to clients. Conducting exploratory data analysis, data profiling, and feature engineering to prepare datasets for predictive modeling is another key aspect of your role. Evaluating model performance, optimizing algorithms, and ensuring robustness and accuracy in predictions are critical tasks. To excel in this role, you are required to have a Bachelor's or master's degree in data science, statistics, computer science, engineering, or a related quantitative field with a strong academic record. Proficiency in programming languages such as Python and R, along with a deep understanding of libraries like TensorFlow, Scikit-learn, and Pandas, is essential. Strong experience with SQL and cloud-based data processing environments like AWS (Redshift, Athena, S3) is preferred, as well as familiarity with Jupyter Notebooks/SageMaker. Demonstrated ability to build data visualizations and communicate insights through various tools, strong analytical skills, experience in hypothesis testing, A/B testing, and statistical analysis are required. Additionally, you should possess exceptional communication and presentation skills to explain complex data science concepts to non-technical stakeholders. A strong problem-solving mindset and the ability to adapt and innovate in a dynamic consulting environment are also key attributes for this role.,

The Data Analyst role at our organization is a pivotal position that involves transforming intricate challenges into actionable insights by harnessing the power of data. As a Data Analyst, you will work collaboratively with diverse teams to analyze extensive datasets, construct predictive models, and devise data-centric solutions that elevate strategic decision-making processes and propel organizational advancement. We seek an inquisitive, imaginative individual who is enthusiastic about utilizing statistical and machine learning methodologies to address real-world issues. This role demands a proactive approach, strong implementation capabilities, and the capacity to operate autonomously. In addition to executing the existing strategy, you will be expected to contribute to its evolution. We are in search of candidates who aspire to make contributions to the broader data architecture community and emerge as thought leaders in this field. Embracing a diversity of perspectives is a core value for us, and we are dedicated to assembling a team that mirrors the diversity of our global community. Your responsibilities will include collecting, processing, and analyzing substantial volumes of structured and unstructured data from various sources. Your insights will play a key role in guiding strategic decisions and enhancing technology operations and metrics. This will involve improving resource utilization, enhancing system reliability, and reducing technical debt. Close collaboration with business stakeholders will be essential to grasp their objectives, formulate analytical questions, and translate requirements into data-driven solutions. Engaging in exploratory data analysis (EDA) to reveal patterns, trends, and actionable insights will be a crucial aspect of your work. Furthermore, you will be tasked with visualizing and communicating findings through engaging reports, dashboards, presentations, and data storytelling techniques tailored to both technical and non-technical audiences. Working closely with engineering teams, you will deploy predictive models into production environments, ensuring their reliability, scalability, and performance. Continuous monitoring, evaluation, and enhancement of model performance will be part of your ongoing responsibilities, requiring you to implement improvements as needed. Staying abreast of the latest research, tools, and best practices in data science, machine learning, and artificial intelligence is integral to this role. Additionally, fostering a culture of experimentation, continuous learning, and innovation within the organization is a key expectation. To be successful in this role, you should possess at least 10 years of experience as a practitioner in data engineering or a related field, along with a Bachelor's or Master's degree in computer science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field. Strong programming skills in languages like Python or R, familiarity with SQL, and knowledge of distributed computing frameworks such as Spark and Hadoop are advantageous. Proficiency in data visualization tools like Matplotlib, PowerBI, and Tableau is required. A solid grasp of probability, statistics, hypothesis testing, and data modeling concepts is essential. Experience with cloud platforms (e.g., AWS, GCP, Azure) for data storage, processing, and model deployment is beneficial. Excellent communication and collaboration skills are a must, including the ability to explain complex technical concepts to diverse audiences. Strong attention to detail, analytical thinking, and problem-solving abilities are also key attributes for this role. Preferred qualifications include experience in large-scale data science projects or in industry domains like finance, healthcare, retail, or technology. Familiarity with MLOps practices, model versioning, monitoring tools, natural language processing (NLP), computer vision, or time-series analysis is advantageous. Contributions to open-source projects or publications in relevant conferences/journals are a plus. Developing and maintaining data pipelines, ETL processes, and implementing machine learning algorithms and statistical models aimed at analyzing technology metrics are additional preferred qualifications. Hands-on experience with machine learning libraries and frameworks such as scikit-learn, TensorFlow, Keras, PyTorch, or XGBoost is desirable. Key competencies for this role include analytical expertise, technical proficiency in machine learning, statistical modeling, and data engineering principles, effective communication skills, collaboration abilities, and a dedication to innovative problem-solving and experimentation with novel technologies.,

The TTS Analytics team offers analytical insights to the Product, Pricing, Client Experience, and Sales functions within the global Treasury & Trade Services business. The primary focus of the team is to address business problems related to driving acquisitions, cross-sell opportunities, revenue growth, and enhancing client experience. By extracting relevant insights, identifying business opportunities, and developing analytical frameworks, the team utilizes big data tools and machine learning algorithms to build predictive models and other solutions. Additionally, the team designs go-to-market strategies for a diverse range of business challenges. As a Business Analytics Analyst (C11) in the TTS Analytics team, you will be reporting to the AVP/VP leading the team. Your role will involve conducting various analyses throughout the year to address business problems across the client life cycle, including acquisition, engagement, client experience, and retention for the TTS business. This will require leveraging multiple analytical approaches, tools, and techniques while working with various data sources such as client profiles, engagement data, transactions, revenue data, digital data, and unstructured data like call transcripts to deliver data-driven insights to business and functional stakeholders. Qualifications: - Bachelors or Masters Degree with 5-8 years of experience in data analytics Must have: - Marketing analytics experience - Experience in addressing business problems related to sales/marketing strategy optimization, pricing optimization, client experience, cross-sell, and retention - Proficiency in various analytical methods including hypothesis testing, segmentation, time series forecasting, test vs. control comparison, and predictive modeling using Machine Learning Good to have: - Experience in financial services - Proficiency in working with complex data from different sources - Experience in unstructured data analysis using Natural Language Processing (NLP)/Text Mining Skills: Analytical Skills: - Strong logical reasoning and problem-solving abilities - Proficiency in translating business problems into analytical tasks and turning analytical findings into actionable business insights - Ability to formulate analytical methodology, identify trends and patterns within data, and manipulate data from big data environments Tools and Platforms: - Proficiency in Python/R, SQL - Experience in PySpark, Hive, Scala - Proficiency in MS Excel, PowerPoint Good to have: - Experience with Tableau Soft Skills: - Ability to identify, articulate, and solve complex business problems while presenting solutions in a structured and simplified manner to management - Excellent communication and interpersonal skills - Strong process/project management skills - Ability to coach and mentor junior team members - Contribution to organizational initiatives including competency development, training, and organizational building activities This role falls under the Decision Management Job Family Group and the Business Analysis Job Family. It is a full-time position that requires the most relevant skills as listed above. For additional complementary skills, please refer to the details provided or contact the recruiter. If you require a reasonable accommodation due to a disability to access our search tools or apply for a career opportunity, please review the Accessibility at Citi guidelines. For more information on Citibank's EEO Policy Statement and the Know Your Rights poster, please refer to the respective documents.,

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The ACOE's delivery framework is designed to provide relevant and contextual insights for data-driven decisions. This includes a one-stop solution for metrics, dashboards driving actionable insights, optimization of performance, measuring pre/post feature impact, sizing the ROI of opportunities, prioritization of opportunities, anomaly-driven alerting mechanisms, root cause analysis of metric deviation, and exploratory hypothesis testing. We are looking for a hands-on Staff, Advanced Analytics who has demonstrated success in building an analytics team with functional expertise in building analytical solutions. Be a trusted partner to product teams and business leaders, across marketplace teams through providing insights, recommendations, and enabling data driven decisions. This role will sit under the Advanced Analytics family and support Product and Business leaders within our CS organization. As a Staff, Advanced Analytics, you will act as a data thought partner to product and business leaders across marketplace teams by providing insights, recommendations, and enabling data-informed decisions. Your responsibilities will include driving day-to-day product analytics, developing analytical solutions, and gaining a deep understanding of how guests and hosts interact with our CS products to enhance the customer experience. Your typical day will involve owning the product analytics roadmap, prioritizing and delivering solutions in the Contact Center Product space. You will lead end-to-end measurement for AI systems, collaborate with engineering on defining scale logging, and evaluate A/B and causal tests to quantify the impact of AI features and optimizations. Additionally, you will translate insights into strategic recommendations for senior leaders, shape product priorities through data, and mentor the team in AI analytics and experiment best practices. To be successful in this role, you should have 12+ years of industry experience and a degree (Masters or PhD is a plus) in a quantitative field. Expert communication and collaboration skills are essential, along with proficiency in Python, SQL, A/B testing platforms, and best practices. You should also have strong expertise in statistical analysis, machine learning techniques, and familiarity with AI systems and observability best practices. Airbnb is committed to diversity and inclusion, encouraging individuals from all backgrounds to apply. We believe that diverse perspectives drive innovation and creativity, enabling us to develop the best products and solutions.,

About The Role Entity :- Accenture Strategy & Consulting Team :- Strategy & Consulting Global Network Practice :- Marketing Analytics Job location :- Gurgaon About S&C - Global Network :- Accenture Applied Intelligence practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. WHATS IN IT FOR YOU? As part of our Analytics practice, you will join a worldwide network of over 20,000 smart and driven colleagues experienced in leading statistical tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance. Accenture will continually invest in your learning and growth. You'll work with MMM experts, and Accenture will support you in growing your own tech stack and certifications In Applied intelligence you will understands the importance of sound analytical decision-making, relationship of tasks to the overall project, and executes projects in the context of a business performance improvement initiative. What you would do in this role Working through the phases of project Define data requirements for creating a model and understand the business problem Clean, aggregate, analyze, interpret data and carry out quality analysis of it 5+ years of advanced experience of Market Mix Modeling and related concepts of optimizing promotional channels and budget allocation Experience in working with non linear optimization techniques. Proficiency in Statistical and Probabilistic methods such as SVM, Decision-Trees, Bagging and Boosting Techniques, Clustering Hands on experience in python data-science and math packages such as NumPy , Pandas, Sklearn, Seaborne, Pycaret, Matplotlib Development of AI/ML models Develop and Manage data pipelines Develop and Manage Data within different layers of Azure/ Snowflake Aware of common design patterns for scalable machine learning architectures, as well as tools for deploying and maintaining machine learning models in production. Knowledge of cloud platforms and usage for pipelining and deploying and scaling marketing mix models. Working knowledge of MMM optimizer and its intricacies Awareness of MMM application development and backend engine integration will be preferred Working along with the team and consultant/manager Well versed with creating insights presentations and client ready decks. Should be able to mentor and guide a team of 10-15 people under him/her Manage client relationships and expectations, and communicate insights and recommendations effectively Capability building and thought leadership Logical Thinking Able to think analytically, use a systematic and logical approach to analyze data, problems, and situations. Notices discrepancies and inconsistencies in information and materials. Task Management Advanced level of task management knowledge and experience. Should be able to plan own tasks, discuss and work on priorities, track and report progress Qualification Who we are looking for? 5+ years of work experience in consulting/analytics with reputed organization is desirable. Master degree in Statistics/Econometrics/ Economics or B Tech/M Tech or Masters/M Tech in Computer Science or M.Phil/Ph.D in statistics/econometrics or related field from reputed college Must have knowledge of SQL and Python language and at-least one cloud-based technologies (Azure, AWS, GCP) Must have good knowledge of Market mix modeling techniques and optimization algorithms and applicability to industry data Must have data migration experience from cloud to snowflake (Azure, GCP, AWS) Managing sets of XML, JSON, and CSV from disparate sources. Manage documentation of data models, architecture, and maintenance processes Have an understanding of econometric/statistical modeling and analysis techniques such as regression analysis, hypothesis testing, multivariate statistical analysis, time series techniques, optimization techniques, and statistical packages such as R, Python, Java, SQL, Spark etc. Working knowledge in Machine Learning algorithms like Random Forest, Gradient Boosting, Neural Network etc. Proficient in Excel, MS word, PowerPoint, etc. Strong client and team management and planning of large-scale projects with risk assessment Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

About The Role JR: R00229254 Experience: 11-15 Years Educational Qualification: Bachelors or Masters degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or other Quantitative field. --------------------------------------------------------------------- Job Title - S&C Global Network - AI - Healthcare Analytics - Senior Manager Management Level: 6-Senior Manager Location: Bangalore/Gurgaon Must-have skills: R,Phython,SQL,Spark,Tableau ,Power BI Good to have skills: Ability to leverage design thinking, business process optimization, and stakeholder management skills. Job Summary : This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Roles & Responsibilities: Provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. As part of our Data & AI practice, you will join a worldwide network of smart and driven colleagues experienced in leading AI/ML/Statistical tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance. WHATS IN IT FOR YOU? An opportunity to work on high-visibility projects with top Pharma clients around the globe. Potential to Co-create with leaders in strategy, industry experts, enterprise function practitioners, and business intelligence professionals to shape and recommend innovative solutions that leverage emerging technologies. Ability to embed responsible business into everythingfrom how you service your clients to how you operate as a responsible professional. Personalized training modules to develop your strategy & consulting acumen to grow your skills, industry knowledge, and capabilities. Opportunity to thrive in a culture that is committed to accelerating equality for all. Engage in boundaryless collaboration across the entire organization. What you would do in this role Lead proposals, and business development efforts and coordinate with other colleagues to cross-sell/ up-sell Life Sciences offerings to existing as well as potential clients. Lead client discussions, developing new industry Point of View (PoV), re-usable assets (tools) Collaborate closely with cross-functional teams including Data engineering, technology, and business stakeholders to identify opportunities for leveraging data to drive business solutions. Lead and manage teams to deliver transformative and innovative client projects. Guide teams on analytical and AI methods and approaches Manage client relationships to foster trust, deliver value, and build the Accenture brand Drive consulting practice innovation and thought leadership in your area of specialization Support strategies and operating models focused on some business units and assess likely competitive responses. Also, assess implementation readiness and points of greatest impact. Execute a transformational change plan aligned with the clients business strategy and context for change. Engage stakeholders in the change journey and build commitment to change. Professional & Technical Skills: - Relevant experience in the required domain. - Strong analytical, problem-solving, and communication skills. - Ability to work in a fast-paced, dynamic environment. Proven experience in cross-sell/ up-sell Leverage ones hands-on experience of working across one or more of these areas such as real-world evidence data, R&D clinical data, and digital marketing data. Experience with handling Datasets like Komodo, RAVE, IQVIA, Truven, Optum, SHS, Specialty Pharmacy, PSP, etc. Experience in building and deployment of Statistical Models/Machine Learning including Segmentation & predictive modeling, hypothesis testing, multivariate statistical analysis, time series techniques, and optimization. Excellent analytical and problem-solving skills, with a data-driven mindset. Ability to solve complex business problems and deliver client delight. Strong writing skills to build points of view on current industry trends. Good Client handling skills; able to demonstrate thought leadership & problem-solving skills. Additional Information: - Opportunity to work on innovative projects. - Career growth and leadership exposure. About Our Company | Accenture Qualification Experience: 11-15 Years Educational Qualification: Bachelors or Masters degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or other Quantitative field.

Job Posting TitleSR. DATA SCIENTIST Band/Level5-2-C Education ExperienceBachelors Degree (High School +4 years) Employment Experience5-7 years At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world. Job Overview Solves complex problems and help stakeholders make data- driven decisions by leveraging quantitative methods, such as machine learning. It often involves synthesizing large volume of information and extracting signals from data in a programmatic way. Roles & Responsibilities Key Responsibilities Design, train, and evaluate supervised & unsupervised models (regression, classification, clustering, uplift). Apply automated hyperparameter optimization (Optuna, HyperOpt) and interpretability techniques (SHAP, LIME). Perform deep exploratory data analysis (EDA) to uncover patterns & anomalies. Engineer predictive features from structured, semistructured, and unstructured data; manage feature stores (Feast). Ensure data quality through rigorous validation and automated checks. Build hierarchical, intermittent, and multiseasonal forecasts for thousands of SKUs. Implement traditional (ARIMA, ETS, Prophet) and deeplearning (RNN/LSTM, TemporalFusion Transformer) approaches. Reconcile forecasts across product/category hierarchies; quantify accuracy (MAPE, WAPE) and bias. Establish model tracking & registry (MLflow, SageMaker Model Registry). Develop CI/CD pipelines for automated retraining, validation, and deployment (Airflow, Kubeflow, GitHub Actions). Monitor data & concept drift; trigger retuning or rollback as needed. Design and analyze A/B tests, causal inference studies, and Bayesian experiments. Provide statisticallygrounded insights and recommendations to stakeholders. Translate business objectives into datadriven solutions; present findings to exec & nontech audiences. Mentor junior data scientists, review code/notebooks, and champion best practices. Desired Candidate Minimum Qualifications M.S. in Statistics (preferred) or related field such as Applied Mathematics, Computer Science, Data Science. 5+ years building and deploying ML models in production. Expertlevel proficiency in Python (Pandas, NumPy, SciPy, scikitlearn), SQL, and Git. Demonstrated success delivering largescale demandforecasting or timeseries solutions. Handson experience with MLOps tools (MLflow, Kubeflow, SageMaker, Airflow) for model tracking and automated retraining. Solid grounding in statistical inference, hypothesis testing, and experimental design. Preferred / NicetoHave Experience in supplychain, retail, or manufacturing domains with highgranularity SKU data. Familiarity with distributed data frameworks (Spark, Dask) and cloud data warehouses (BigQuery, Snowflake). Knowledge of deeplearning libraries (PyTorch, TensorFlow) and probabilistic programming (PyMC, Stan). Strong datavisualization skills (Plotly, Dash, Tableau) for storytelling and insight communication. Competencies ABOUT TE CONNECTIVITY TE Connectivity plc (NYSETEL) is a global industrial technology leader creating a safer, sustainable, productive, and connected future. Our broad range of connectivity and sensor solutions enable the distribution of power, signal and data to advance next-generation transportation, energy networks, automated factories, data centers, medical technology and more. With more than 85,000 employees, including 9,000 engineers, working alongside customers in approximately 130 countries, TE ensures that EVERY CONNECTION COUNTS. Learn more atwww.te.com and onLinkedIn , Facebook , WeChat, Instagram and X (formerly Twitter). WHAT TE CONNECTIVITY OFFERS: We are pleased to offer you an exciting total package that can also be flexibly adapted to changing life situations - the well-being of our employees is our top priority! Competitive Salary Package Performance-Based Bonus Plans Health and Wellness Incentives Employee Stock Purchase Program Community Outreach Programs / Charity Events IMPORTANT NOTICE REGARDING RECRUITMENT FRAUD TE Connectivity has become aware of fraudulent recruitment activities being conducted by individuals or organizations falsely claiming to represent TE Connectivity. Please be advised that TE Connectivity never requests payment or fees from job applicants at any stage of the recruitment process. All legitimate job openings are posted exclusively on our official careers website at te.com/careers, and all email communications from our recruitment team will come only from actual email addresses ending in @te.com . If you receive any suspicious communications, we strongly advise you not to engage or provide any personal information, and to report the incident to your local authorities. Across our global sites and business units, we put together packages of benefits that are either supported by TE itself or provided by external service providers. In principle, the benefits offered can vary from site to site.

Prescience Decision Solutions is looking for Senior Data Analyst/Senior Business Analyst to join our dynamic team and embark on a rewarding career journey The Senior Data Analyst is responsible for analyzing large datasets, interpreting data, and providing actionable insights to support business decision-making They will work closely with cross-functional teams to identify data needs, design data collection methods, perform data analysis, and communicate findings to stakeholders The Senior Data Analyst plays a crucial role in driving data-driven strategies and improving overall business performance Key Responsibilities:Collect, clean, and transform large datasets from various sources to ensure data accuracy and integrity Analyze complex datasets using statistical techniques and data mining methods to identify trends, patterns, and insights Interpret and communicate findings to both technical and non-technical stakeholders through reports, visualizations, and presentations Collaborate with cross-functional teams to understand business requirements and develop data analysis plans to address specific objectives Develop and maintain data models, dashboards, and reports to provide ongoing performance metrics and KPIs Identify data quality issues, perform data validation, and implement data cleaning and data normalization processes Utilize data visualization tools (e g , Tableau, Power BI) to create interactive dashboards and visual representations of data Stay updated with industry trends, emerging technologies, and best practices in data analysis and data management Identify opportunities to optimize data collection, analysis, and reporting processes, and implement efficient and automated solutions Mentor and provide guidance to junior data analysts, fostering their professional growth and development Qualifications and Skills:Bachelor's degree in statistics, mathematics, computer science, or a related field A master's degree is a plus X years of experience as a Data Analyst, preferably in a senior or lead role Proficiency in statistical analysis tools such as R, Python, or SAS Strong knowledge of data analysis techniques, including regression analysis, hypothesis testing, and data mining Experience with data visualization tools, such as Tableau, Power BI, or QlikView Solid understanding of SQL for data manipulation and extraction Familiarity with data warehousing concepts and database systems (e g , SQL Server, Oracle) Excellent analytical and problem-solving skills, with attention to detail Strong communication and presentation skills, with the ability to effectively communicate complex data insights to non-technical stakeholders Ability to work independently and collaboratively in a fast-paced environment, handling multiple projects and priorities

You will be responsible for conducting Exploratory Data Analysis (EDA) and data wrangling to clean, process, and visualize large datasets. Your primary task will involve developing and implementing Machine Learning models for demand forecasting using Python. Additionally, you will work on feature engineering to enhance model accuracy and performance. Handling time-series data processing for efficient forecasting will be a crucial part of your role. Collaborating with cross-functional teams is essential to deliver actionable insights from data analysis. You will utilize Excel for basic data manipulation tasks like pivoting, creating formulas (e.g., VLOOKUP, SUMIF), and performing aggregation functions. Working with SQL to query databases and write complex queries with JOIN, GROUP BY, WHERE clauses, and subqueries is a part of your daily responsibilities. Your main objective will be to provide solutions and insights for business forecasting within project timelines. Architecting and building end-to-end machine learning solutions, which include data extraction, feature engineering, model development, validation, deployment, and monitoring, based on statistical analysis, are critical aspects of the role. Developing and maintaining robust MLOps pipelines to automate and scale model deployment to ensure workflow reliability is also part of your duties. Applying statistical techniques such as hypothesis testing, A/B testing, and regression analysis to validate models and enhance decision-making are necessary. Your ability to translate complex business problems into analytical solutions using statistical reasoning and provide expert guidance on data science use cases will be valuable. Qualifications: Education: You should hold a Master's degree in Statistics, Mathematics, Computer Science, Data Science, or a related field. A PhD is preferred. Experience: A minimum of 7 years of experience as a Data Scientist or in a related role is required. Technical Skills: - Proficiency in Python and R programming languages - Experience with machine learning libraries like scikit-learn, TensorFlow, and PyTorch - Familiarity with data visualization libraries such as matplotlib, seaborn, and Tableau - Knowledge of big data technologies including Hadoop, Spark, and SQL - Experience with cloud computing platforms like AWS, Azure, or GCP is preferred Preferred Skills: - Experience with natural language processing (NLP) and deep learning techniques - Proficiency in time series analysis and forecasting - Knowledge of data mining and predictive modeling - Strong communication and presentation skills - Experience with Agile development methodologies Please note that the above qualifications and skills are essential for excelling in this position.,