5336 Data Visualization Jobs - Page 40

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

Job Summary We are looking for a passionate and technically skilled AI Intern to support our AI/ML initiatives. This role offers hands-on experience in building intelligent systems, working with datasets, and contributing to innovative AI solutions. Qualification Bachelors Degree in Computer Science,IT, AI, ML or a related field. Technical Skills Required Programming Languages: Proficiency in Python; familiarity with R, Java, or C++ is a plus. Machine Learning Libraries: scikit-learn, XGBoost, LightGBM. Deep Learning Frameworks: TensorFlow, PyTorch, Keras. Data Handling: pandas, NumPy, SQL, Apache Spark (basic). Data Visualization: Matplotlib, Seaborn, Plotly. Natural Language Processing (NLP): spaCy, NLTK, Hugging Face Transformers. Computer Vision (optional): OpenCV, torchvision. Model Deployment: Flask/FastAPI, Docker, basic understanding of REST APIs. Version Control: Git, GitHub/GitLab. Cloud Platforms (preferred): AWS (SageMaker) or Azure ML. Tools Environments: Jupyter Notebooks, VS Code, Google Colab. Familiarity with MLOps concepts and tools (e.g., Kubeflow , Docker , Kubernetes , MLflow , DVC) is a bonus. Strong foundation in statistics, linear algebra, and probability. Job Responsibilities Assist in developing, training, and evaluating machine learning and deep learning models. Perform data preprocessing, feature engineering, and exploratory data analysis (EDA). Support the deployment and monitoring of AI models in production environments. Conduct research on state-of-the-art AI techniques and present findings. Collaborate with cross-functional teams to integrate AI solutions into products. Document code, experiments, and project outcomes clearly and concisely.

Job Summary We are seeking a highly motivated individual for the PE-Maps role with a focus on enhancing communication and collaboration within our team. The ideal candidate will have excellent English speaking skills and a keen interest in the ISV domain. This entry-level position offers an opportunity to work from our office during day shifts contributing to our innovative projects. Responsibilities Communicate effectively with team members and stakeholders to ensure project goals are met. Collaborate with cross-functional teams to develop and implement project plans. Assist in the preparation of project documentation and reports. Participate in team meetings and contribute ideas for process improvements. Support the team in identifying and resolving project-related issues. Monitor project progress and provide regular updates to the project manager. Conduct research and analysis to support project decision-making. Utilize strong English communication skills to facilitate clear and concise information exchange. Engage with the ISV domain to gain insights and apply them to project tasks. Maintain a high level of professionalism and integrity in all interactions. Adapt to changing project requirements and priorities as needed. Demonstrate a willingness to learn and grow within the role. Ensure all project activities align with the companys objectives and values. Qualifications Possess excellent English speaking and communication skills. Demonstrate a strong interest in the ISV domain. Show ability to work effectively in a team-oriented environment. Exhibit strong organizational and time management skills. Display a proactive approach to problem-solving and decision-making. Have a basic understanding of project management principles. Be eager to learn and develop new skills in a professional setting.

KPMG India is looking for Senior - Data Science to join our dynamic team and embark on a rewarding career journey Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

KPMG India is looking for Analyst - Regtech Analyst to join our dynamic team and embark on a rewarding career journey The Senior Analyst plays a crucial role in driving data-driven decision-making processes within the organization This position involves analyzing complex data sets, generating actionable insights, and providing strategic recommendations to support key business initiatives Key Responsibilities:Data Analysis:Conduct in-depth analysis of large and complex datasets to extract meaningful insights Utilize statistical and data visualization tools to present findings in a clear and concise manner Strategic Planning:Collaborate with cross-functional teams to understand business objectives and provide analytical support for strategic initiatives Develop and maintain models to support forecasting, budgeting, and other planning processes Reporting and Dashboards:Design and create comprehensive reports and dashboards to track key performance indicators (KPIs) and metrics Automate reporting processes to improve efficiency and accuracy Trend Analysis:Identify trends and patterns in data to help anticipate opportunities and challenges Provide insights on market trends, competitor analysis, and industry benchmarks Decision Support:Assist senior management in making informed decisions by providing data-driven recommendations Evaluate the impact of proposed strategies on business outcomes Process Improvement:Identify areas for process improvement and efficiency gains based on data analysis Collaborate with teams to implement changes and measure the impact

KPMG India is looking for Analyst - Intelligent Automation Packaged Product to join our dynamic team and embark on a rewarding career journeyThe Senior Analyst plays a crucial role in driving data-driven decision-making processes within the organization. This position involves analyzing complex data sets, generating actionable insights, and providing strategic recommendations to support key business initiatives.Key Responsibilities:Data Analysis:Conduct in-depth analysis of large and complex datasets to extract meaningful insights.Utilize statistical and data visualization tools to present findings in a clear and concise manner.Strategic Planning:Collaborate with cross-functional teams to understand business objectives and provide analytical support for strategic initiatives.Develop and maintain models to support forecasting, budgeting, and other planning processes.Reporting and Dashboards:Design and create comprehensive reports and dashboards to track key performance indicators (KPIs) and metrics.Automate reporting processes to improve efficiency and accuracy.Trend Analysis:Identify trends and patterns in data to help anticipate opportunities and challenges.Provide insights on market trends, competitor analysis, and industry benchmarks.Decision Support:Assist senior management in making informed decisions by providing data-driven recommendations.Evaluate the impact of proposed strategies on business outcomes.Process Improvement:Identify areas for process improvement and efficiency gains based on data analysis.Collaborate with teams to implement changes and measure the impact.

HSBC electronic data processing india pvt ltd is looking for Consultant Specialist to join our dynamic team and embark on a rewarding career journeyThe Consultant Specialist plays a critical role in providing specialized expertise and consulting services to clients or within the organization. This position involves offering strategic insights, solving complex problems, and delivering high-quality solutions tailored to the unique needs of clients or projects.Key Responsibilities:Consultation and Analysis:Conduct in-depth analysis and assessment of client needs, challenges, and objectives.Offer expert advice and guidance to clients on relevant industry trends, best practices, and strategies.Develop comprehensive solutions to address client issues and achieve desired outcomes.Project Management:Plan and execute consultancy projects, ensuring adherence to timelines and budgets.Monitor project progress, identify potential risks, and implement mitigation strategies.Collaborate with cross-functional teams to deliver integrated solutions.Data Analysis and Research:Collect, analyze, and interpret data to provide data-driven insights.Conduct research to stay updated on industry developments and emerging trends.Create reports and presentations to communicate findings effectively.Client Relationship Management:Cultivate strong, long-term relationships with clients and stakeholders.Communicate regularly with clients to ensure their needs are met and expectations are exceeded.Identify opportunities for additional services and business growth.Training and Knowledge Sharing:Provide training, workshops, or presentations to clients or internal teams as needed.Share expertise and knowledge with colleagues to enhance overall team capabilities.

Cp\Were Hiring: Cloud Data Architect Azure DatabricksC/p\Cp\Key Responsibilities:C / p\Cul\Cli\Design and implement scalable, efficient cloud data models using Azure Data Lake and Azure Databricks.C/li\Cli\Ensure data quality, consistency, and integrity across all data models and platforms.C/li\Cli\Define and enforce development standards and best practices.C/li\Cli\Architect and model Business Intelligence (BI) and Analytics solutions to support data-driven decision-making.C / li\Cli\Collaborate with stakeholders to gather business requirements and translate them into technical specifications.C/li\Cli\Develop and maintain data models, data integration pipelines, and data warehousing solutions.C/li\Cli\Build and manage ETL (Extract, Transform, Load) processes to ensure timely and accurate data availability.C / li\C / ul\Cp\Required Qualifications:C / p\Cul\Cli\Proven experience as a Data Scientist, Data Architect, Data Analyst, or similar role.C/li\Cli\Strong understanding of data warehouse architecture and principles.C/li\Cli\Proficiency in SQL and experience with database systems such as Oracle, SQL Server, or PostgreSQL.C/li\Cli\Hands-on experience with Databricks for data engineering and SQL warehouse MUST.C/li\Cli\Familiarity with data visualization tools like Power BI or Qlik.C/li\Cli\Experience with data warehousing platforms such as Snowflake or Amazon Redshift.C/li\Cli\Strong analytical and problem-solving skills.C/li\Cli\Excellent communication and collaboration abilities.C / li\Cli\Bachelordegree in Computer Science, Engineering, or a related field; Masterdegree preferred.C/li\Cli\Demonstrated expertise in BI and Analytics architecture, ETL design, and data integration workflows.C/li\C/ul\Cp\Cbr\C/p

Curate and manage datasets to ensure they meet quality and compliance standards. Develop and implement data governance policies and procedures. Conduct data profiling and quality assessments to identify discrepancies and improve data quality. Collaborate with data producers and consumers to understand data needs and requirements. Create and maintain metadata documentation to enhance data discoverability and usability. Monitor and evaluate data curation processes and recommend improvements. Support data integration and data migration projects as needed. Stay updated on best practices in data curation, management, and governance. Skillsets: Experience in using, testing, modifying APIs Experience on JIRA and Salesforce Proficiency in data manipulation tools and programming languages (e.g., PLSQL, Python) Strong communication skills and the ability to work collaboratively with cross-functional teams Experience with data visualization using Power BI

Who we are About Stripe About the team As Stripe s user base and global footprint grows dramatically, we have distinctly unique support problems resulting from both our type of scale and the type of businesses we partner with. The Stripe Delivery Center (SDC) will provide operational leverage and expand Stripe s portfolio of operational capabilities to support the scaled needs for external users and internal Stripe teams. This role will be part of the Marketing Services team in the SDC that is accountable for the delivery of all aspects of email demand and lead generation activities, lead nurturing, and conversion programs. We are looking for someone who is passionate about Marketing Operations and thrives in dynamic, complex environments. You are naturally curious, collaborative and comfortable operating in ambiguity and finding creative solutions. You will act in a player-coach capacity and will be accountable for supporting associates in delivering post-campaign summaries, mapping prospect journeys within our systems, and helping to enrich contact lists from events to ensure accurate outreach and supporting Performance Marketing Ad Operations goals and mentoring in subject matter expertise. You will manage a small team of MOps & Ad Ops specialists. Responsibilities COversee campaign performance reporting, analyzing and delivering insights on campaign performance to assess lead quality and persona alignment. Summarize Marketing Qualified Lead (MQL) data post-campaign, evaluating lead qualification processes to inform future campaigns. Coordinate with regional marketing teams to audit, clean, and enrich contact lists based on event registration requirements. Generate reports and dashboards in Salesforce to monitor campaign attribution and sales follow-up effectiveness. Monitor lead flow and system performance, identifying opportunities for improvement in the lead management process. Create detailed lead lists for event attendees, ensuring compliance with Stripe s privacy policy for CRM uploads. Enrich third-party account lists using various data sources to support marketing efforts. Assist marketing teams in setting up campaigns in Salesforce, including building UTMs for campaign tracking. Ensure high-quality standards in all deliverables with careful attention to detail. Build and manage ads across platforms such as Meta, LinkedIn, Google, and Bing, overseeing pacing and reporting for ongoing campaigns. Conduct data uploads and pull queries for analysis, while leveraging Stripes marketing data tables and Google Sheets. Collaborate with the performance marketing team, creative agencies, and other marketing operations as needed. Minimum requirements Bachelors degree in Marketing, Business, or a related field preferred. 7+ years of experience in marketing operations or a related field. 5+years of experience with Marketo. Proficiency in Salesforce with experience in reporting and dashboard creation. Strong analytical skills to interpret data and provide actionable insights. Excellent attention to detail and organizational skills. Collaborative mindset with the ability to manage multiple projects effectively. Familiarity with CRM systems and data management best practices. Knowledge of digital marketing principles and campaign management. Proficiency in paid channels (Meta, LinkedIn, Google, Bing) preferred; relevant certifications are a plus. Skilled in data management using Excel or Google Sheets; SQL experience is a plus. Experience with marketing technology and data visualization tools. Strong time management skills and ability to meet tight deadlines. Excellent communication skills and passion for the latest advertising platform trends and best practices. Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico and Bengaluru, India work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible. Team New Financial Products Job type Full time

Data Analyst Job Description: Interpret data, analyze results using statistical techniques, and provide ongoing reports. Develop and maintain dashboards and visualizations using tools like Power BI, Tableau, or similar. Identify, analyze, and interpret trends or patterns in complex data sets. Work closely with management to prioritize business and information needs. Acquire data from primary or secondary sources and maintain databases/data systems. Filter and clean data, and review reports and performance indicators to locate and correct problems. Provide actionable insights and recommendations based on data analysis. Experience Range: 0 - 1 years Educational Qualifications: Any graduation Skills Required: Data Analysis

Performance Marketing Specialist (02 04 Years) - GALTech Technologies Pvt. Ltd | Software Company India | Dubai Performance Marketing Specialist (02 04 Years) Position title Performance Marketing Specialist (02 04 Years) Description Join our dynamic team as a Performance Marketing Specialist! Youll manage campaigns, analyze data, and develop creative strategies on platforms like Google Ads and Meta Ads, contributing to the success of our digital marketing efforts. Roles and Responsibilities: 1. Plan and implement performance marketing campaigns across platforms like Google Ads, Meta (Facebook & Instagram) Ads, LinkedIn, and other relevant channels. 2. Monitor and analyze campaign performance to ensure KPIs and ROI targets are met. 3. Conduct A/B testing on creatives, ad formats, and landing pages to optimize conversion rates. 4. Allocate and manage campaign budgets effectively for cost-efficient advertising. 5. Forecast and track spending across multiple platforms. 6. Perform market research to identify new growth opportunities and refine target audience strategies. 7. Stay informed on industry trends, competitor strategies, and emerging channels. 8. Present campaign results, insights, and recommendations to senior management and stakeholders. Skills and Requirements: 1. Bachelor s degree 2. 2+ years of experience in performance marketing or digital advertising. 3. Proficiency in ad platforms like Google Ads, Meta Ads, and programmatic tools. 4. Strong analytical skills with expertise in Google Analytics, Excel, and data visualization tools. 5. Effective written and verbal communication skills. 6. Experience in audience targeting, campaign optimization, and budget management. . Strong analytical skills with expertise in Google Analytics, Excel, and data visualization tools Position: Performance Marketing Specialist (02 04 Years) Only Pdf or Docx file allowed Thank you for submitting your application. We will contact you shortly!

Profile- Power BI developer Exp- 8-10 years Location - Noida JD- Skills and Responsibilities: 1. Proficiency in Power BI: You should be able to create, publish, and maintain Power BI reports and dashboards. 2. DAX and Power Query: Youll likely be writing DAX formulas and using Power Query for data transformation. 3. Data Modeling: Experience in data modeling and integrating reporting components from multiple data sources is expected. 4. Data Analysis: You should be able to gather, analyze, and present data effectively. 5. SQL: Familiarity with SQL and data warehousing concepts is highly beneficial. 6. ETL Processes: Understanding ETL processes is also valuable. 7. Project Management: Experienced professionals may be involved in project management aspects. 8. Emerging Trends: Staying updated with emerging trends like AI/ML integration, cloud-based BI, and data visualization techniques is crucial. 9. Data Governance and Security:Understanding data governance and security practices is increasingly important. Key Skills - Changes, Enhancement And New Dashboard Building In QLIKVIEW And QLIKSENCE PowerBI Application Apply Now Apply For Job

UI/UX Designer Job | 5+ Yrs Exp | Night Shift | Panchkula Join Our Clan UI/UX Designer Description Job Description We are looking for an experienced and creative UI/UX Designer with over 5 years of hands-on experience. This role involves designing user-first experiences across web platforms, social assets, and enterprise products. The ideal candidate brings a strong understanding of user behavior, a solid design portfolio, and the ability to translate complex requirements into intuitive, accessible designs. You will be working closely with cross-functional teams, including product managers, developers, and other designers, to craft digital experiences that are both functional and delightful. Skills Key Skills 5+ years of experience as a UX or UI/UX Designer. Strong portfolio showcasing user flows, wireframes, prototypes, and final UI mockups. Expertise in Figma, Adobe XD, Sketch, InDesign, and Illustrator. Ability to create platform-specific social media designs and assets. Strong understanding of UX principles and user-centered design methods. Experience designing responsive and mobile-first web applications. Knowledge of HTML, CSS, or front-end development is a plus. Familiarity with accessibility standards (WCAG) and inclusive design. Hands-on experience with usability testing and user research. Strong communication and collaboration skills. Ability to use AI tools effectively in creating visual and digital assets. Comfortable working in Agile or Scrum-based teams. Experience working in B2B or SaaS environments. Understanding of marketing design for high-performance campaigns. Familiarity with tools like Miro, Jira, and Confluence. Knowledge of interaction design and animation principles. Exposure to data visualization and dashboard design. Understanding of brand consistency and digital style guides. Responsibilities Roles & Responsibilities Conduct user research to understand needs, behaviors, and pain points. Create user flows, personas, and information architectures. Design wireframes, mockups, and interactive prototypes. Develop creative social media assets aligned with platform standards. Collaborate with product and development teams throughout the project lifecycle. Test and refine designs based on user feedback and usability results. Ensure all designs meet accessibility, brand, and usability standards. Contribute to the design systems and maintain reusable components. Advocate for design thinking and user-first approaches across teams. Work during the 4:00 PM to 1:00 AM IST shift. Position: UI/UX Designer Thank you for submitting your application. We will contact you shortly! Stay updated with us Life at Grazitti Share Your Profile We are always looking for the best talent to join our team Thank you for sharing your profile with us. If it aligns with our requirements, we will reach out to you for the next steps in the process.

Before you apply to a job, select your language preference from the options available at the top right of this page. Job Description: Job Title: FA Senior Admin Assistant (Grade 7) Job Summary: We are seeking a highly organized and detail-oriented administrative assistant to perform a variety of general administrative tasks. This role includes preparing reports using various software packages, compiling information from multiple sources, and managing small-scale projects. The ideal candidate will have understanding of Logistics flow and be proficient in Microsoft Excel, with knowledge of billing processes. Key Responsibilities: Prepare reports and presentations using Microsoft Excel and other software tools Maintain confidentiality when dealing with sensitive information Assist with billing processes and documentation Provide general administrative support as needed Qualifications: Proficiency in Microsoft Excel (advanced functions such as pivot tables, formulas, and data visualization) Strong attention to detail and ability to handle confidential information Excellent organizational and communication skills Familiarity with billing processes is a plus

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

Company: Marsh Description: We are seeking a talented individual to join our Data Science team at Marsh. This role will be based in Mumbai. This is a hybrid role that has a requirement of working at least three days a week in the office. Senior Manager - Data Science (AI - CoE) This role at Knowledge Services aims to provide colleagues with an exposure towards key risks faced by businesses and utilize Artificial intelligence to manage, transfer or mitigate them. Incumbent is expected to be an expert of Generative AI (OpenAI APIs), Prompt Engineering, Data Science algorithms, Business Analytics and Data Manipulation. Incumbent will also have an opportunity to contribute to cutting edge analytics platform and products. Expertise in Python is a must. Experience with Insurance or Banking industry is a plus. This position is for an individual contributor in AI and Data Science, who will develop and implement leading-edge techniques in artificial intelligence, machine learning, predictive modeling, and natural language processing as applied in commercial insurance and risk management. This position consults with senior colleagues on complex financial and statistical analyses, and develops approaches for new, market-leading AI-based tools. We will count on you to Understand and refine the Math and Statistics behind the complex AI models Build AI and machine learning algorithms based on the business ask Keep up pace with new trends in the AI world Mine and analyze data to drive optimization and implement business strategies Deploy APIs on the cloud platforms by understanding the technical ask Develop statistical custom data models and algorithms from scratch to enhance current value proposition and new product development What you need to have: Develops solutions based on Large Language Models, Advanced transformers, Advanced deep learning/Neural networks models Expertise in image based advanced models, Object detection, Video/Image processing, multimodal RAGs and other image and video models Develops and deploys API based business solutions on AWS platforms Coordinates with technology colleagues within and outside the team for support, manage, enhance and retrains deployed models Keeps pace with the fast-evolving world of AI, large language models and other type of AI solutions in the market and able to apply research level knowledge to benefit Marsh advisory businesses Designs, develops and contributes to Data architecture for complex enterprise level applications Deploys solutions on AWS cloud platforms Understands business problems to create an approach that starts with determining structured and unstructured data needs and availability, builds AI/ML models, and finalizes with results that unlock insight for clients/colleagues, deploy these solutions on web framework and enterprise wide platforms Demonstrates skill in advanced statistical analysis, data mining, and/or research techniques, combined with broader awareness of the business and ongoing research, while functioning in a collaborative role with the Data Science team and across the wider organization Stays current with ongoing research in the field and brings new approaches to the team Coaches team members on the delivery of AI-based tools and analyses and presentation of findings Masters Degree in Engineering, Computer Science, Data Science or related field 7+ years of experience in the field of Data Science, AI research or similar fields Expert Data Scientist, including expertise with AI and machine learning model building Ability to influence others within and outside of the job function regarding approach and procedures Superior detail orientation, excellent communication and interpersonal skills Expertise of modern programming languages such as Python, including NumPy, Keras, TensorFlow, SQL, and PyTorch etc Familiar with Hugging face and is library of models What makes you stand out Building, training and deploying advanced models from the scratch to the production Business impact with AI models Understanding of insurance and risk management Knowledge and demonstrated experience of advance AI concepts like training language, voice, image or computer vision models Experience of building data visualization in Plotly/Dash/D3.js Hands on experience with stochastic or econometric modelling Why join our team: We help you be your best through professional development opportunities, interesting work and supportive leaders. We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities. Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being. Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one anchor day per week on which their full team will be together in person.

Company: Oliver Wyman Description: Oliver Wyman DNA team is now looking to hire a Senior Data Analytics Specialist - we are looking for individuals with strong experience in Power BI and Tableau OW DNA Overview The Oliver Wyman DNA is a distinguished center of excellence for business analytics and data analytics within Oliver Wyman. This group leverages data and information to provide business insights to Oliver Wyman consulting teams driving positive outcomes and tangible impact for Oliver Wymans clients. The group combines cutting edge data science expertise with core consulting expertise to augment engagement teams with analytical firepower to deliver outstanding results. Key Responsibilities: Design and create interactive dashboards to effectively communicate data insights to stakeholders. Gather and extract data from various databases, Excel, and other relevant sources to support BI reporting and analysis. Engage with stakeholders to understand their reporting needs and define key performance indicators (KPIs) and ensure alignment with business objectives. Coordinate with various stakeholders to understand the data structure, collect, clean, transform, validate, and visualize datasets, ensuring the integrity of our data flows Develop data models to identify relationships and trends within the data, enhancing the understanding of business performance. Perform analysis in SQL and Python to derive actionable insights and support data-driven decision-making. Maintain and optimize existing BI reports and dashboards, ensuring accuracy and relevance of the information presented. Manage the design, development, and delivery of self-service data infrastructure Identify and manage dependencies and risks across various analytics datasets and models Education: Bachelors degree in science, Finance, Mathematics, Economics or equivalent. MS or Certificate courses in analytics preferred Experience: Overall experience of 2+ years in business intelligence tools such as Power BI, Tableau. Excellent analytical and problem-solving skills with proven ability to deliver actionable insights and proficiency in data modelling and visualization skills. Proven experience with data automation, creating dashboards in Power BI and Tableau and analytical models. Strong written and verbal communication skills with demonstrated ability to interact effectively with all levels of stakeholders (both internal and external) Fast learner with ability to learn and pick up a new tool/ platform quickly Advanced skills in MS-office, along with familiarity with Gen AI and other analytical tools preferred Experience in data analytics tools such as SQL and python is preferred Willingness to travel as required to meet client needs. Oliver Wyman, a business of Marsh McLennan (NYSEMMC), is a management consulting firm combining deep industry knowledge with specialized expertise to help clients optimize their business, improve operations and accelerate performance. Marsh McLennan is a global leader in risk, strategy and people, advising clients in 130 countries across four businessesMarsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit oliverwyman.com, or follow on LinkedIn and X. Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one anchor day per week on which their full team will be together in person.

Company: Oliver Wyman Description: Oliver Wyman DNA team is now looking to hire a Lead Data Analytics Specialist based in our Hyderabad office. OW DNA Overview The Oliver Wyman DNA is a distinguished center of excellence for business analytics and data analytics within Oliver Wyman. This group leverages data and information to provide business insights to Oliver Wyman consulting teams driving positive outcomes and tangible impact for Oliver Wymans clients. The group combines cutting edge data science expertise with core consulting expertise to augment engagement teams with analytical firepower to deliver outstanding results. Key Responsibilities: Serve as the primary analytical resource for client teams, building trusted relationships with key stakeholders. Collaborate with senior team members to identify risks and growth opportunities, utilizing analytical insights for client benefit. Extract and manipulate data from various sources using SQL and Python for business intelligence reporting. Engage with stakeholders to understand reporting needs and align KPIs with strategic objectives. Coordinate with stakeholders to collect, clean, and validate datasets, ensuring data integrity through coding techniques. Develop and implement data models in SQL and Python to uncover trends and enhance business performance insights. Conduct in-depth analyses with SQL and Python to provide actionable insights for client decision-making. Maintain and optimize BI reports through coding improvements to ensure accuracy and relevance. Stay updated on market trends and best practices in data analytics to enhance service offerings and quality standards. Mentor junior team members in analytical coding practices, fostering a collaborative learning environment. Education: Bachelors degree in science, Finance, Mathematics, Economics or equivalent. MS or Certificate courses in analytics preferred Experience: Over 4+ years of experience in data analytics, focused on SQL and Python coding. Proficient in data analytics tools such as SQL and Python, with a solid track record of managing complex analytical projects Strong analytical and problem-solving skills, delivering actionable insights through data modelling and analysis Excellent client-facing abilities, building relationships with senior stakeholders and influencing decision-makers. Strong written and verbal communication skills, effectively engaging with stakeholders at all levels. Adaptive learner with the ability to rapidly adopt new tools and platforms, including knowledge of Gen AI Entrepreneurial mindset with a collaborative approach to problem-solving and a commitment to mentoring and developing talent. Familiarity with creating visualizations in Power BI and Tableau is a plus. Oliver Wyman, a business of Marsh McLennan (NYSEMMC), is a management consulting firm combining deep industry knowledge with specialized expertise to help clients optimize their business, improve operations and accelerate performance. Marsh McLennan is a global leader in risk, strategy and people, advising clients in 130 countries across four businessesMarsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit oliverwyman.com, or follow on LinkedIn and X. Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one anchor day per week on which their full team will be together in person.

Company: Marsh Description: Mercer is hiring for below position for Gurgaon locationAnalyst Survey Administration What can you expectThis role is for the Data Analyst in the compensation consulting team What is in it for youThe position offers good career advancement opportunities, supported by training and professional development as well as access to the firms global network We will count on you to Client-related activities contact clients during the survey cycle, respond to client ad-hoc queries Support to the market consultants supports participation solicitation, data collection material distribution & follow-up on data submissions, datavalidation and closure of client queries with support from mentor, resolving results acess related issues and respond to ad-hoc queries Internal administrative tasks - update client participation database, ensure that all the documentation and record keeping are complete What do you need to have Graduate in any discipline Comes with 1 year of experience as a data analyst Good to have HR background Minimum 12 months experience as Analyst(B1)/Senior Analyst(B2) Should have at least On-Track or equivalent rating in last appraisal. Should not be under any Performance Counselling Plan or had any official disciplinary action within the last 3 months. Should not have applied for any other IJP in the last 3 months What makes you stand out Good understanding of various areas in HR Excellent interpersonal and communication skills Dynamic, motivated, flexible and result-oriented personality with the ability to perform under pressure Mercer believes in building brighter futures by redefining the world of work, reshaping retirement and investment outcomes, and unlocking real health and well-being. Mercers more than 20,000 employees are based in 43 countries and the firm operates in over 130 countries. Mercer is a business of Marsh McLennan (NYSEMMC), the worlds leading professional services firm in the areas of risk, strategy and people, with more than 85,000 colleagues and annual revenue of over $23 billion. Through its market-leading businesses including YOUR NEXT CAREER MOVEMarsh, Guy Carpenter and Oliver Wyman, Marsh McLennan helps clients navigate an increasingly dynamic and complex environment. For more information, visit mercer.com. Follow Mercer on LinkedIn and X. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one anchor day per week on which their full team will be together in person Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one anchor day per week on which their full team will be together in person.