46 Dplyr Jobs

Job Description: We are looking for a highly skilled and passionate R Programming Online Trainer to join our training team. The ideal candidate should have in-depth knowledge of R programming, statistical analysis, and data visualization, along with the ability to deliver engaging online sessions to learners of various skill levels. As an online trainer, you will be responsible for designing course content, delivering interactive training sessions, and mentoring learners to achieve their learning goals in R. Roles & Responsibilities: Deliver high-quality online training sessions on R programming, data analysis, and visualization. Design, prepare, and update course materials, assignments, and case studies. Explain R programming concepts such as data types, functions, control structures, loops, and packages in a clear and simplified manner. Teach advanced R topics including data manipulation, statistical modeling, machine learning, and integration with other tools. Provide hands-on exercises, real-world use cases, and project-based learning. Track learners’ progress and provide feedback, guidance, and support. Stay updated with the latest trends in R programming, data science, and analytics. Foster an interactive and engaging virtual learning environment. Required Skills & Qualifications: Strong proficiency in R programming with practical knowledge of data analysis, visualization, and statistical techniques. Experience with libraries/packages like dplyr, ggplot2, tidyr, caret, Shiny, and others. Good understanding of data science workflows, machine learning concepts, and statistical methods. Excellent communication and presentation skills. Ability to explain complex concepts in a simple, learner-friendly manner. Educational & Professional Requirements: Bachelor’s or Master’s degree in Computer Science, Statistics, Data Science, Mathematics, or a related field. Industry experience in data analysis, data science, or R programming projects is an added advantage.

About us Optiply is at the forefront of three rapidly expanding sectors: Software as a Service, Artificial Intelligence, and E-commerce. With our intelligent purchasing software, we empower over 300 web shops and wholesalers to make smarter buying decisions, using predictive analytics to optimize inventory management. Job Description As our Forecasting Analyst (R Specialist) at Optiply, you will be the go-to expert on our data team, responsible for the statistical and machine learning models that power our platform. You will be at the heart of our mission to help e-commerce businesses thrive by owning the development, maintenance, and improvement of our forecasting algorithms. You’ll work closely with data scientists, backend developers, and product teams to ensure our models are robust, accurate, and seamlessly integrated. This is what you'll be doing Own the end-to-end lifecycle of our forecasting models—from design and development to validation and maintenance—using your deep expertise in R. Proactively optimize and refactor existing R code for enhanced performance, scalability, and accuracy. Collaborate with backend developers to integrate your R models into our production systems, helping to package them into APIs or microservices. Work with our Customer Success and Product teams to translate business requirements and customer needs into robust technical forecasting solutions. Support data processing and ETL pipelines to ensure high-quality data inputs for your models. Uphold high standards of code quality, rigorous testing, and clear documentation for all your work. Stay current with the latest research and techniques in time series forecasting and statistical modeling. This is who we’re looking for You have 3–6 years of professional experience in a role focused on statistical modeling, quantitative analysis, or time series forecasting. Expert-level proficiency in R for statistical analysis, data manipulation (e.g., dplyr, data.table), and forecasting (e.g., forecast, fable, tidymodels). Demonstrated, hands-on experience building and deploying forecasting models and a strong theoretical understanding of time series analysis or inventory optimization principles. Good working knowledge of Python, primarily for scripting, data handling, or collaborating with engineering teams. Comfortable working with data from various sources (SQL, APIs, flat files). Familiarity with DevOps tools and best practices (Docker, Git, CI/CD pipelines) is a strong plus. Experience working in a production environment and collaborating across teams. You are self-driven, proactive, and comfortable working in a fast-paced, international environment. Nice to Have Exposure to cloud platforms (AWS, GCP, or Azure). Prior experience in a SaaS, e-commerce, or supply chain tech company. This it what we offer Competitive Compensation Package: Reflects your skills and contributions. Holistic Work-Life Harmony: We value your personal time and promote a healthy work-life balance. Comprehensive Health Coverage: Robust insurance plans for your peace of mind. Investment in Professional Growth: We invest in your development with paid training programs. Adaptable Work Hours: We offer flexibility in your work schedule. Hybrid Work Model: Enjoy a blend of remote and in-office work. Strategic Career Development: We provide personalized growth plans and advancement opportunities. Tailored Workspace Setup: Get a high-quality PC, monitor, keyboard, and other essentials. Social Fridays: Wind down the week with casual drinks and foster team camaraderie. This Job Description made your day? Then send us your CV in English and get prepared to meet our team!

About Us Optiply is at the forefront of three rapidly expanding sectors: Software as a Service, Artificial Intelligence, and E-commerce. With our intelligent purchasing software, we empower over 300 web shops and wholesalers to make smarter buying decisions, using predictive analytics to optimize inventory management. Job Description As our Forecasting Analyst (R Specialist) at Optiply, you will be the go-to expert on our data team, responsible for the statistical and machine learning models that power our platform. You will be at the heart of our mission to help e-commerce businesses thrive by owning the development, maintenance, and improvement of our forecasting algorithms. You’ll work closely with data scientists, backend developers, and product teams to ensure our models are robust, accurate, and seamlessly integrated. This Is What You'll Be Doing Own the end-to-end lifecycle of our forecasting models—from design and development to validation and maintenance—using your deep expertise in R. Proactively optimize and refactor existing R code for enhanced performance, scalability, and accuracy. Collaborate with backend developers to integrate your R models into our production systems, helping to package them into APIs or microservices. Work with our Customer Success and Product teams to translate business requirements and customer needs into robust technical forecasting solutions. Support data processing and ETL pipelines to ensure high-quality data inputs for your models. Uphold high standards of code quality, rigorous testing, and clear documentation for all your work. Stay current with the latest research and techniques in time series forecasting and statistical modeling. This Is Who We’re Looking For You have 3–6 years of professional experience in a role focused on statistical modeling, quantitative analysis, or time series forecasting. Expert-level proficiency in R for statistical analysis, data manipulation (e.g., dplyr, data.table), and forecasting (e.g., forecast, fable, tidymodels). Demonstrated, hands-on experience building and deploying forecasting models and a strong theoretical understanding of time series analysis or inventory optimization principles. Good working knowledge of Python, primarily for scripting, data handling, or collaborating with engineering teams. Comfortable working with data from various sources (SQL, APIs, flat files). Familiarity with DevOps tools and best practices (Docker, Git, CI/CD pipelines) is a strong plus. Experience working in a production environment and collaborating across teams. You are self-driven, proactive, and comfortable working in a fast-paced, international environment. Nice to Have Exposure to cloud platforms (AWS, GCP, or Azure). Prior experience in a SaaS, e-commerce, or supply chain tech company. This It What We Offer Competitive Compensation Package: Reflects your skills and contributions. Holistic Work-Life Harmony: We value your personal time and promote a healthy work-life balance. Comprehensive Health Coverage: Robust insurance plans for your peace of mind. Investment in Professional Growth: We invest in your development with paid training programs. Adaptable Work Hours: We offer flexibility in your work schedule. Hybrid Work Model: Enjoy a blend of remote and in-office work. Strategic Career Development: We provide personalized growth plans and advancement opportunities. Tailored Workspace Setup: Get a high-quality PC, monitor, keyboard, and other essentials. Social Fridays: Wind down the week with casual drinks and foster team camaraderie. This Job Description made your day? Then send us your CV in English and get prepared to meet our team!

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of yourself. Your unique voice and perspective are valued to help EY become even better. Join us to build an exceptional experience for yourself and contribute to creating a better working world for all. EY's Consulting Services is a unique, industry-focused business unit providing integrated services leveraging deep industry experience and strong functional and technical capabilities. The Data and Analytics team at EY's Consulting Practice solves complex issues and seizes opportunities to deliver better outcomes for businesses, now and in the future. As a Shiny R Developer, you will play a crucial role in developing high-quality solutions for real-world use cases. You should have 3-7 years of experience and possess the following skills and attributes: - Minimum 2 years of hands-on experience with basic and advanced R and R module development - Minimum 1 year of hands-on experience with Shiny for R/POSIT, developing applications for real use-cases - Experience with gargoyle, r6 classes, ggplot, dplyr - Proficiency in using DBI for postgres db interaction - Familiarity with testing tool "testthat" and working with websockets We are looking for individuals with commercial acumen, technical expertise, and a willingness to learn in a fast-moving environment. Joining our team means being part of a market-leading, multi-disciplinary group of professionals globally, working with leading businesses across various industries. Working at EY offers: - Inspiring and meaningful projects - Education, coaching, and personal development opportunities - Support, coaching, and feedback from engaging colleagues - Opportunities for skill development and career progression - Freedom and flexibility in handling your role EY is dedicated to building a better working world by creating long-term value for clients, people, and society while fostering trust in the capital markets. Our diverse teams in over 150 countries provide trust through assurance and help clients grow, transform, and operate. Join us in asking better questions and finding new answers to the complex issues facing the world today.,

When you join Verizon You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What You Will Be Doing... Commercial Data & Analytics is part of the Verizon Global Services (VGS) organization. The team supports initiatives to uncover actionable insights that drive business value. As the resident expert you will identify business problems, draft hypotheses, define success criteria, size experiments, and analyze overall test results. You will also partner across different teams to ensure alignment on test parameters and data sourcing. As a member of this team, your responsibilities will include: Lead the experimentation lifecycle from end-to-end, including hypothesis formulation, experimental design (e.g., A/B, multivariate), implementation oversight, statistical analysis, and insightful recommendation. Serve as a thought leader and mentor on experimentation, A/B testing, and causal inference, establishing best practices and elevating the team's analytical capabilities Crafting high-quality experimentation deliverables including measurement plans, reporting requirements, and test results. Partner closely with product, marketing, and engineering teams to translate ambiguous business questions into precise, testable hypotheses. Champion statistical best practices throughout the organization, ensuring all tests are properly powered, results are interpreted correctly, and conclusions are statistically sound. Translate complex experimental results into clear, actionable business recommendations and communicate them effectively to stakeholders at all levels, including senior leadership. What We’re Looking For… You are a deeply curious and statistically-minded scientist who is passionate about finding truth in data. You are not just a modeler; you are a scientific method champion who understands that well-designed experiments are the most reliable way to drive impactful change. You Will Need To Have A Bachelor’s degree with four or more years of experience. Six or more years of progressive experience as a Data Analyst, with a proven track record of leading initiatives in A/B testing, experimentation, and conversion rate optimization. Deep expertise in statistical hypothesis testing (e.g., t-tests, ANOVA, Chi-squared), experimental design (A/B, MVT), and power/sample size calculations. Expert-level proficiency in Python or R, with extensive experience using statistical and data manipulation libraries (e.g., statsmodels, scipy, pandas in Python; dplyr, rstatix in R). Mastery of SQL for complex data extraction and cohort analysis from large-scale data warehouses. Exceptional ability to explain statistical concepts like p-values, confidence intervals, and statistical significance to non-technical stakeholders to drive data-informed decisions. Excellent collaboration skills, with a history of working effectively with cross-functional teams to design and execute tests. Even better if you have one or more of the following: Expertise in advanced causal inference methods (e.g., Difference-in-Differences, Regression Discontinuity, Propensity Score Matching). Practical experience with commercial or open-source experimentation platforms (e.g., Optimizely, Statsig, VWO, or building in-house tools). Knowledge of multi-armed bandit algorithms and their application in real-time optimization. Experience in a product-led growth (PLG) or e-commerce environment where A/B testing is a core driver of strategy. Experience with Bayesian statistics and its application to experimental analysis. Proficiency with cloud computing platforms (e.g., AWS, GCP, Azure) and version control using Git. Experience building insightful dashboards and reports in tools like Tableau, Looker, or Qlik to monitor experiment results. Where you’ll be working In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. Scheduled Weekly Hours 40 Equal Employment Opportunity Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.

When you join Verizon You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What You Will Be Doing... Commercial Data & Analytics is part of the Verizon Global Services (VGS) organization. The team supports initiatives to uncover actionable insights that drive business value. As the resident expert you will identify business problems, draft hypotheses, define success criteria, size experiments, and analyze overall test results. You will also partner across different teams to ensure alignment on test parameters and data sourcing. As a member of this team, your responsibilities will include: Lead the experimentation lifecycle from end-to-end, including hypothesis formulation, experimental design (e.g., A/B, multivariate), implementation oversight, statistical analysis, and insightful recommendation. Serve as a thought leader and mentor on experimentation, A/B testing, and causal inference, establishing best practices and elevating the team's analytical capabilities Crafting high-quality experimentation deliverables including measurement plans, reporting requirements, and test results. Partner closely with product, marketing, and engineering teams to translate ambiguous business questions into precise, testable hypotheses. Champion statistical best practices throughout the organization, ensuring all tests are properly powered, results are interpreted correctly, and conclusions are statistically sound. Translate complex experimental results into clear, actionable business recommendations and communicate them effectively to stakeholders at all levels, including senior leadership. What We’re Looking For… You are a deeply curious and statistically-minded scientist who is passionate about finding truth in data. You are not just a modeler; you are a scientific method champion who understands that well-designed experiments are the most reliable way to drive impactful change. You Will Need To Have A Bachelor’s degree with four or more years of experience. Six or more years of progressive experience as a Data Analyst, with a proven track record of leading initiatives in A/B testing, experimentation, and conversion rate optimization. Deep expertise in statistical hypothesis testing (e.g., t-tests, ANOVA, Chi-squared), experimental design (A/B, MVT), and power/sample size calculations. Expert-level proficiency in Python or R, with extensive experience using statistical and data manipulation libraries (e.g., statsmodels, scipy, pandas in Python; dplyr, rstatix in R). Mastery of SQL for complex data extraction and cohort analysis from large-scale data warehouses. Exceptional ability to explain statistical concepts like p-values, confidence intervals, and statistical significance to non-technical stakeholders to drive data-informed decisions. Excellent collaboration skills, with a history of working effectively with cross-functional teams to design and execute tests. Even better if you have one or more of the following: Expertise in advanced causal inference methods (e.g., Difference-in-Differences, Regression Discontinuity, Propensity Score Matching). Practical experience with commercial or open-source experimentation platforms (e.g., Optimizely, Statsig, VWO, or building in-house tools). Knowledge of multi-armed bandit algorithms and their application in real-time optimization. Experience in a product-led growth (PLG) or e-commerce environment where A/B testing is a core driver of strategy. Experience with Bayesian statistics and its application to experimental analysis. Proficiency with cloud computing platforms (e.g., AWS, GCP, Azure) and version control using Git. Experience building insightful dashboards and reports in tools like Tableau, Looker, or Qlik to monitor experiment results. Where you’ll be working In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. Scheduled Weekly Hours 40 Equal Employment Opportunity Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.

Chennai, India Hyderabad, India Bangalore, India Job ID: R-1083311 Apply prior to the end date: September 20th, 2025 When you join Verizon You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What you will be doing... Commercial Data & Analytics is part of the Verizon Global Services (VGS) organization. The team supports initiatives to uncover actionable insights that drive business value. As the resident expert you will identify business problems, draft hypotheses, define success criteria, size experiments, and analyze overall test results. You will also partner across different teams to ensure alignment on test parameters and data sourcing. As a member of this team, your responsibilities will include: Lead the experimentation lifecycle from end-to-end, including hypothesis formulation, experimental design (e.g., A/B, multivariate), implementation oversight, statistical analysis, and insightful recommendation. Serve as a thought leader and mentor on experimentation, A/B testing, and causal inference, establishing best practices and elevating the team's analytical capabilities Crafting high-quality experimentation deliverables including measurement plans, reporting requirements, and test results. Partner closely with product, marketing, and engineering teams to translate ambiguous business questions into precise, testable hypotheses. Champion statistical best practices throughout the organization, ensuring all tests are properly powered, results are interpreted correctly, and conclusions are statistically sound. Translate complex experimental results into clear, actionable business recommendations and communicate them effectively to stakeholders at all levels, including senior leadership. What we’re looking for… You are a deeply curious and statistically-minded scientist who is passionate about finding truth in data. You are not just a modeler; you are a scientific method champion who understands that well-designed experiments are the most reliable way to drive impactful change. You will need to have: A Bachelor’s degree with four or more years of experience. Six or more years of progressive experience as a Data Analyst, with a proven track record of leading initiatives in A/B testing, experimentation, and conversion rate optimization. Deep expertise in statistical hypothesis testing (e.g., t-tests, ANOVA, Chi-squared), experimental design (A/B, MVT), and power/sample size calculations. Expert-level proficiency in Python or R, with extensive experience using statistical and data manipulation libraries (e.g., statsmodels, scipy, pandas in Python; dplyr, rstatix in R). Mastery of SQL for complex data extraction and cohort analysis from large-scale data warehouses. Exceptional ability to explain statistical concepts like p-values, confidence intervals, and statistical significance to non-technical stakeholders to drive data-informed decisions. Excellent collaboration skills, with a history of working effectively with cross-functional teams to design and execute tests. Even better if you have one or more of the following: Expertise in advanced causal inference methods (e.g., Difference-in-Differences, Regression Discontinuity, Propensity Score Matching). Practical experience with commercial or open-source experimentation platforms (e.g., Optimizely, Statsig, VWO, or building in-house tools). Knowledge of multi-armed bandit algorithms and their application in real-time optimization. Experience in a product-led growth (PLG) or e-commerce environment where A/B testing is a core driver of strategy. Experience with Bayesian statistics and its application to experimental analysis. Proficiency with cloud computing platforms (e.g., AWS, GCP, Azure) and version control using Git. Experience building insightful dashboards and reports in tools like Tableau, Looker, or Qlik to monitor experiment results. Where you’ll be working In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. Scheduled Weekly Hours 40 Equal Employment Opportunity Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics. Apply Now Save Saved Open sharing options Share Related Jobs Senior Engineer Consultant-Data Science Save Madhapur, India, +1 other location Technology Princ Engr-Data Engineering Save Madhapur, India Technology Engineer III Spec-Data Engineering Save Madhapur, India, +1 other location Technology Shaping the future. Connect with the best and brightest to help innovate and operate some of the world’s largest platforms and networks.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Associate Analyst, R Programmer-1 Overview The Mastercard Economics Institute (MEI) is an economics lab powering scale at Mastercard by owning economic thought leadership in support of Mastercard’s efforts to build a more inclusive and sustainable digital economy The Economics Institute was launched in 2020 to analyze economic trends through the lens of the consumer to deliver tailored and actionable insights on economic issues for customers, partners and policymakers The Institute is composed of a team of economists and data scientists that utilize & synthesize the anonymized and aggregated data from the Mastercard network together with public data to bring powerful insights to life, in the form of 1:1 presentation, global thought leadership, media participation, and commercial work through the company’s product suites About the Role We are looking for an R programmer to join Mastercard’s Economics Institute, reporting to the team lead for Economics Technology. An individual who will: create clear, compelling data visualisations that communicate economic insights to diverse audiences develop reusable R functions and packages to support analysis and automation create and format analytical content using R Markdown and/or Quarto design and build scalable Shiny apps develop interactive visualisations using JavaScript charting libraries (e.g. Plotly, Highcharts, D3.js) or front-end frameworks (e.g. React, Angular, Vue.js)work with databases and data platforms (eg. SQL, Hadoop) write clear, well-documented code that others can understand and maintain collaborate using Git for version control All About You proficient in R and the RStudio IDE proficient in R packages like dplyr for data cleaning, transformation, and aggregation familiarity with dependency management and documentation in R (e.g. roxygen2) familiar with version control concepts and tools (e.g. Git, GitHub, Bitbucket) for collaborative development experience writing SQL and working with relational databases creative and passionate about data, coding, and technology strong collaborator who can also work independently organized and able to prioritise work across multiple projects comfortable working with engineers, product owners, data scientists, economists Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Associate Analyst, R Programmer-1 Overview The Mastercard Economics Institute (MEI) is an economics lab powering scale at Mastercard by owning economic thought leadership in support of Mastercard’s efforts to build a more inclusive and sustainable digital economy The Economics Institute was launched in 2020 to analyze economic trends through the lens of the consumer to deliver tailored and actionable insights on economic issues for customers, partners and policymakers The Institute is composed of a team of economists and data scientists that utilize & synthesize the anonymized and aggregated data from the Mastercard network together with public data to bring powerful insights to life, in the form of 1:1 presentation, global thought leadership, media participation, and commercial work through the company’s product suites About The Role We are looking for an R programmer to join Mastercard’s Economics Institute, reporting to the team lead for Economics Technology. An individual who will: create clear, compelling data visualisations that communicate economic insights to diverse audiences develop reusable R functions and packages to support analysis and automation create and format analytical content using R Markdown and/or Quarto design and build scalable Shiny apps develop interactive visualisations using JavaScript charting libraries (e.g. Plotly, Highcharts, D3.js) or front-end frameworks (e.g. React, Angular, Vue.js)work with databases and data platforms (eg. SQL, Hadoop) write clear, well-documented code that others can understand and maintain collaborate using Git for version control All About You proficient in R and the RStudio IDE proficient in R packages like dplyr for data cleaning, transformation, and aggregation familiarity with dependency management and documentation in R (e.g. roxygen2) familiar with version control concepts and tools (e.g. Git, GitHub, Bitbucket) for collaborative development experience writing SQL and working with relational databases creative and passionate about data, coding, and technology strong collaborator who can also work independently organized and able to prioritise work across multiple projects comfortable working with engineers, product owners, data scientists, economists Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Product Analyst - II About the job About Chargebee: Chargebee is a subscription billing and revenue management platform powering some of the fastest-growing brands around the world today, including Calendly, Hopin, Pret-a-Manger, Freshworks, Okta, Study.com, and others. Thousands of SaaS and subscription-first businesses process over billions of dollars in revenue every year through the Chargebee platform. Headquartered in San Francisco, USA, our 500+ team members work remotely throughout the world, including India, the Netherlands, Paris, Spain, Australia, and the USA. Chargebee has raised over $480 million in capital and is funded by Accel, Sequoia, Tiger Global, Insight Partners, Steadview Capital, and Sapphire Ventures. And we’re on a mission to push the boundaries of subscription revenue operations. Not just ours, but every customer and prospective business on a recurring revenue model. Job Summary: The Chargebee Product Analytics team provides analytical insights and solutions for critical cross-company functions and processes that affect how we show up in the world for our customers, including SaaS Billing, Retention, Customer Focus, and Payments. As a Data Scientist, you can use your quantitative skill set, empathy towards customers, and collaborative spirit to work closely with Product, Ops, Marketing, Engineering, and Finance to provide data-driven insights. In addition, it will allow you to find new opportunities to take our product and business to the next level. As a Product Analyst - II, you'll focus on the following: ● The analysis, manipulation, visualization of data, and data story-telling ● At times you shouldn't hesitate to do data engineering/ETL (extract-transform-load) ● Provide product or business insights and analytical strategy ● There will be an additional focus on the design and analysis of experiments, and pseudo-control techniques Roles and Responsibilities: ● Refine ambiguous questions and generate new hypotheses about the product and business through a deep understanding of the data, our customers, and our business. ● Design experiments and interpret the results to draw detailed and impactful conclusions. ● Define how our teams measure success by developing Key Performance Indicators, Input /Output metrics, and other customers/business metrics in close partnership with product and other subject areas such as engineering, operations, and marketing ● Collaborate with data scientists, BI teams, and engineers to build and improve the availability, integrity, accuracy, and reliability of data logging/telemetry, data pipelines, and reporting insights. ● Develop data-driven business insights and work with cross-functional partners to identify opportunities and recommend prioritization of product, growth, retention, and optimization initiatives. Must Haves: ● M.S. or Bachelor's degree in Math, Economics, Statistics, Engineering, Computer Science, or other quantitative fields. (If an M.S. degree, a minimum of 2+ years of industry experience is required, and if a Bachelor's degree, a minimum of 3+ years of industry experience as a Product Analyst, Data Scientist, or equivalent) ● Experience in at least one scripting language (SQL, Python, R, or SAS preferred) ● Basic understanding of experimental design (such as A/B experiments) and statistical methods ● Willingness to get your hands dirty with messy data to identify product opportunities and streamline data pipeline, automate and gain efficiency. ● Ability to communicate effectively and manage relationships with partners coming from both technical and non-technical backgrounds ● Strong story-telling: Distill interesting and hard-to-find insights into a compelling, concise data story ● Experience with experimental design and statistical methods such as causal Inference. ● Strong judgment, critical thinking, and decision-making skills ● Ability to solve complex business problems that cross multiple product/project areas and teams ● Balance attention to detail with swift execution Nice to haves: ● Advanced degrees in Math, Economics, Statistics, Engineering, Computer Science, Operation Research, Quantitative analysis, Machine Learning, or other quantitative fields. ● 5+ years of industry experience in consumer-facing product and data science ● Data Science or Product analytics experience in SaaS companies or the B2B fintech sector. Technical Skillset: SQL (Advanced) : Highly proficient in writing complex SQL queries for data extraction, manipulation, and analysis from various databases. This includes understanding different joins, subqueries, window functions, and optimization techniques. Data Analysis & Interpretation: Strong ability to collect, clean, process, analyze, and interpret large and complex datasets to identify trends, patterns, anomalies, and root causes. Statistical Analysis: Solid understanding of statistical concepts (hypothesis testing, regression, correlation, A/B testing, sampling distributions) and their application to product and business problems. Programming (Python/R): Proficiency in Python or R for data manipulation (Pandas/dplyr), statistical modeling, machine learning (scikit-learn, TensorFlow/PyTorch - depending on the data science depth), and automation of data tasks. Data Visualization : Expertise in creating clear, compelling, and actionable dashboards and reports using tools like Tableau. Ability to tell a story with data. A/B Testing & Experimentation: Experience in designing, executing, and analyzing A/B tests to measure the impact of product changes and new features. Understanding of experimental design principles. Product Analytics Tools: Familiarity with product analytics platforms (e.g., Sentry, Pendo, Google Analytics, Splunk) for tracking user behavior, engagement, and feature adoption. Business & Product Skills: Deep understanding of the B2B SaaS fintech business model, sales cycles, customer journey, and revenue drivers. Product Strategy & Roadmap: Ability to translate data insights into actionable product recommendations and contribute to product strategy and roadmap development. Market Research & Competitive Analysis: Experience in conducting market research, analyzing competitor products and strategies, and identifying market opportunities. User Experience (UX) Understanding: Ability to analyze user behavior data to identify pain points, optimize user flows, and enhance overall user experience. Problem Solving: Highly analytical and methodical approach to identifying problems, breaking them down, and developing data-driven solutions. Soft Skills: Logical Thinking : Exceptional ability to think critically, identify underlying issues, and construct sound arguments based on data. Stakeholder Management : Proven ability to effectively communicate with and manage expectations of diverse stakeholders (product managers, engineers, sales, marketing, leadership). This includes translating complex technical findings into understandable business insights. Communication (Verbal & Written) : Excellent presentation skills, ability to articulate complex concepts clearly and concisely to both technical and non-technical audiences. Strong documentation skills. Collaboration : Ability to work effectively in cross-functional teams, fostering a collaborative environment. Proactive & Curious : A self-starter with a strong sense of curiosity, a desire to dig deeper into data, and a proactive approach to identifying opportunities. Adaptability : Ability to thrive in a fast-paced, dynamic B2B SaaS environment and adapt to evolving priorities. We are Globally Local With a diverse team across four continents, and customers in over 60 countries, you get to work closely with a global perspective right from your own neighborhood. We value Curiosity We believe the next great idea might just be around the corner. Perhaps it’s that random thought you had ten minutes ago. We believe in creating an ecosystem that fosters a desire to seek out hard questions, and then figure out answers to them. Customer! Customer! Customer! Everything we do is driven towards enabling our customers’ growth. This means no matter what you do, you will always be adding real value to a real business problem. It’s a lot of responsibility, but also a lot of fun.

About us Optiply is at the forefront of three rapidly expanding sectors: Software as a Service, Artificial Intelligence, and E-commerce. With our intelligent purchasing software, we empower over 300 web shops and wholesalers to make smarter buying decisions, using predictive analytics to optimize inventory management. Job Description As our Forecasting Analyst (R Specialist) at Optiply, you will be the go-to expert on our data team, responsible for the statistical and machine learning models that power our platform. You will be at the heart of our mission to help e-commerce businesses thrive by owning the development, maintenance, and improvement of our forecasting algorithms. You’ll work closely with data scientists, backend developers, and product teams to ensure our models are robust, accurate, and seamlessly integrated. This is what you'll be doing Own the end-to-end lifecycle of our forecasting models—from design and development to validation and maintenance—using your deep expertise in R. Proactively optimize and refactor existing R code for enhanced performance, scalability, and accuracy. Collaborate with backend developers to integrate your R models into our production systems, helping to package them into APIs or microservices. Work with our Customer Success and Product teams to translate business requirements and customer needs into robust technical forecasting solutions. Support data processing and ETL pipelines to ensure high-quality data inputs for your models. Uphold high standards of code quality, rigorous testing, and clear documentation for all your work. Stay current with the latest research and techniques in time series forecasting and statistical modeling. This is who we’re looking for You have 3–6 years of professional experience in a role focused on statistical modeling, quantitative analysis, or time series forecasting. Expert-level proficiency in R for statistical analysis, data manipulation (e.g., dplyr, data.table), and forecasting (e.g., forecast, fable, tidymodels). Demonstrated, hands-on experience building and deploying forecasting models and a strong theoretical understanding of time series analysis or inventory optimization principles. Good working knowledge of Python, primarily for scripting, data handling, or collaborating with engineering teams. Comfortable working with data from various sources (SQL, APIs, flat files). Familiarity with DevOps tools and best practices (Docker, Git, CI/CD pipelines) is a strong plus. Experience working in a production environment and collaborating across teams. You are self-driven, proactive, and comfortable working in a fast-paced, international environment. Nice to Have Exposure to cloud platforms (AWS, GCP, or Azure). Prior experience in a SaaS, e-commerce, or supply chain tech company. This it what we offer Competitive Compensation Package: Reflects your skills and contributions. Holistic Work-Life Harmony: We value your personal time and promote a healthy work-life balance. Comprehensive Health Coverage: Robust insurance plans for your peace of mind. Investment in Professional Growth: We invest in your development with paid training programs. Adaptable Work Hours: We offer flexibility in your work schedule. Hybrid Work Model: Enjoy a blend of remote and in-office work. Strategic Career Development: We provide personalized growth plans and advancement opportunities. Tailored Workspace Setup: Get a high-quality PC, monitor, keyboard, and other essentials. Social Fridays: Wind down the week with casual drinks and foster team camaraderie. This Job Description made your day? Then send us your CV in English and get prepared to meet our team!

About Us Optiply is at the forefront of three rapidly expanding sectors: Software as a Service, Artificial Intelligence, and E-commerce. With our intelligent purchasing software, we empower over 300 web shops and wholesalers to make smarter buying decisions, using predictive analytics to optimize inventory management. Job Description As our Forecasting Analyst (R Specialist) at Optiply, you will be the go-to expert on our data team, responsible for the statistical and machine learning models that power our platform. You will be at the heart of our mission to help e-commerce businesses thrive by owning the development, maintenance, and improvement of our forecasting algorithms. You’ll work closely with data scientists, backend developers, and product teams to ensure our models are robust, accurate, and seamlessly integrated. This Is What You'll Be Doing Own the end-to-end lifecycle of our forecasting models—from design and development to validation and maintenance—using your deep expertise in R. Proactively optimize and refactor existing R code for enhanced performance, scalability, and accuracy. Collaborate with backend developers to integrate your R models into our production systems, helping to package them into APIs or microservices. Work with our Customer Success and Product teams to translate business requirements and customer needs into robust technical forecasting solutions. Support data processing and ETL pipelines to ensure high-quality data inputs for your models. Uphold high standards of code quality, rigorous testing, and clear documentation for all your work. Stay current with the latest research and techniques in time series forecasting and statistical modeling. This Is Who We’re Looking For You have 3–6 years of professional experience in a role focused on statistical modeling, quantitative analysis, or time series forecasting. Expert-level proficiency in R for statistical analysis, data manipulation (e.g., dplyr, data.table), and forecasting (e.g., forecast, fable, tidymodels). Demonstrated, hands-on experience building and deploying forecasting models and a strong theoretical understanding of time series analysis or inventory optimization principles. Good working knowledge of Python, primarily for scripting, data handling, or collaborating with engineering teams. Comfortable working with data from various sources (SQL, APIs, flat files). Familiarity with DevOps tools and best practices (Docker, Git, CI/CD pipelines) is a strong plus. Experience working in a production environment and collaborating across teams. You are self-driven, proactive, and comfortable working in a fast-paced, international environment. Nice to Have Exposure to cloud platforms (AWS, GCP, or Azure). Prior experience in a SaaS, e-commerce, or supply chain tech company. This It What We Offer Competitive Compensation Package: Reflects your skills and contributions. Holistic Work-Life Harmony: We value your personal time and promote a healthy work-life balance. Comprehensive Health Coverage: Robust insurance plans for your peace of mind. Investment in Professional Growth: We invest in your development with paid training programs. Adaptable Work Hours: We offer flexibility in your work schedule. Hybrid Work Model: Enjoy a blend of remote and in-office work. Strategic Career Development: We provide personalized growth plans and advancement opportunities. Tailored Workspace Setup: Get a high-quality PC, monitor, keyboard, and other essentials. Social Fridays: Wind down the week with casual drinks and foster team camaraderie. This Job Description made your day? Then send us your CV in English and get prepared to meet our team!

Role : R Analytics Support. Mode : Onsite (5 days) (Rotational shift 24-7) NO night shift. Location : Mumbai. Job Summary We are looking for an experienced R Analytics Lead to manage the day-to-day operations of our R-based analytics environment. The role focuses on monitoring the execution of existing R scripts, resolving failures through root cause analysis and data cleaning, supporting business teams with production data requests, and mentoring the R Ops team for better process efficiency and incident handling. Key Responsibilities Monitor Production Jobs : Oversee successful execution of scheduled R scripts; monitor failures, investigate issues, and take corrective actions. Root Cause Analysis : Troubleshoot script failures and identify data or logic issues; perform necessary fixes and re-execute the process to ensure output delivery. Data Cleaning : Handle raw or inconsistent production data by applying proper cleaning techniques to ensure smooth script execution. Production Data Requests : Fulfill various production data and reporting requests raised by business stakeholders using R and SQL. Issue Resolution & Team Support : Act as the go-to person for any technical issues in the R Ops team. Guide and support team members in identifying problems and resolving them. Process Improvement : Identify areas to improve existing R code performance, suggest enhancements, and help automate or simplify routine tasks. Collaboration with Development & QA : Support testing, deployment, and monitoring activities for new script developments or changes in the production environment. Knowledge Sharing : Train and mentor team members on R coding standards, production support practices, database usage, and debugging techniques. Required Qualifications 6+ years of experience in analytics, with at least 4 years in a lead or senior operations/support role. Strong hands-on experience in R programming (especially with packages like dplyr, data.table, readr, lubridate). Proficiency in SQL for data extraction, transformation, and analysis. Experience in handling production support, script monitoring, and issue resolution. Demonstrated ability to lead teams, train junior members, and coordinate across departments. Desirable Skills Familiarity with scheduling tools and database connections in a production environment. Ability to document processes, communicate issues clearly, and interact with business users. (ref:hirist.tech)

About us Optiply is at the forefront of three rapidly expanding sectors: Software as a Service, Artificial Intelligence, and E-commerce. With our intelligent purchasing software, we empower over 300 web shops and wholesalers to make smarter buying decisions, using predictive analytics to optimize inventory management. Job Description As our Forecasting Analyst (R Specialist) at Optiply, you will be the go-to expert on our data team, responsible for the statistical and machine learning models that power our platform. You will be at the heart of our mission to help e-commerce businesses thrive by owning the development, maintenance, and improvement of our forecasting algorithms. You’ll work closely with data scientists, backend developers, and product teams to ensure our models are robust, accurate, and seamlessly integrated. This is what you'll be doing Own the end-to-end lifecycle of our forecasting models—from design and development to validation and maintenance—using your deep expertise in R. Proactively optimize and refactor existing R code for enhanced performance, scalability, and accuracy. Collaborate with backend developers to integrate your R models into our production systems, helping to package them into APIs or microservices. Work with our Customer Success and Product teams to translate business requirements and customer needs into robust technical forecasting solutions. Support data processing and ETL pipelines to ensure high-quality data inputs for your models. Uphold high standards of code quality, rigorous testing, and clear documentation for all your work. Stay current with the latest research and techniques in time series forecasting and statistical modeling. This is who we’re looking for You have 3–6 years of professional experience in a role focused on statistical modeling, quantitative analysis, or time series forecasting. Expert-level proficiency in R for statistical analysis, data manipulation (e.g., dplyr, data.table), and forecasting (e.g., forecast, fable, tidymodels). Demonstrated, hands-on experience building and deploying forecasting models and a strong theoretical understanding of time series analysis or inventory optimization principles. Good working knowledge of Python, primarily for scripting, data handling, or collaborating with engineering teams. Comfortable working with data from various sources (SQL, APIs, flat files). Familiarity with DevOps tools and best practices (Docker, Git, CI/CD pipelines) is a strong plus. Experience working in a production environment and collaborating across teams. You are self-driven, proactive, and comfortable working in a fast-paced, international environment. Nice to Have Exposure to cloud platforms (AWS, GCP, or Azure). Prior experience in a SaaS, e-commerce, or supply chain tech company. This it what we offer Competitive Compensation Package: Reflects your skills and contributions. Holistic Work-Life Harmony: We value your personal time and promote a healthy work-life balance. Comprehensive Health Coverage: Robust insurance plans for your peace of mind. Investment in Professional Growth: We invest in your development with paid training programs. Adaptable Work Hours: We offer flexibility in your work schedule. Hybrid Work Model: Enjoy a blend of remote and in-office work. Strategic Career Development: We provide personalized growth plans and advancement opportunities. Tailored Workspace Setup: Get a high-quality PC, monitor, keyboard, and other essentials. Social Fridays: Wind down the week with casual drinks and foster team camaraderie. This Job Description made your day? Then send us your CV in English and get prepared to meet our team!

About This Role We're seeking a motivated Data Analytics Intern to join our team and dive deep into GitHub repository data. You'll work with large datasets of software repositories, contributor activity, and development patterns to uncover actionable insights that drive our product and engineering decisions. This is an excellent opportunity for students or recent graduates interested in data science, software analytics, and open-source ecosystems to gain hands-on experience with real-world data at scale. What You'll Do Extract and analyze GitHub repository data using APIs and web scraping techniques Build automated data pipelines to collect repository metrics, commit histories, and contributor patterns Create compelling visualizations and dashboards to communicate findings to technical and non-technical stakeholders Conduct statistical analysis on code quality, development velocity, and project health metrics Research trends in programming languages, frameworks, and open-source project adoption Collaborate with engineering teams to identify metrics that matter for software development Present insights and recommendations to leadership based on your analysis What You'll Learn Advanced GitHub API usage and repository mining techniques Large-scale data processing and analysis workflows Data visualization best practices for technical audiences Software development metrics and their business impact Experience with cloud-based analytics platforms Professional data science project management Required Qualifications Currently pursuing or recently completed a degree in Data Science, Computer Science, Statistics, Mathematics, or related field Programming proficiency in Python or R with experience in data manipulation libraries (pandas, dplyr, etc.) Basic understanding of Git and GitHub workflows SQL knowledge for database querying and data extraction Data visualization experience (matplotlib, seaborn, ggplot2, Tableau, or similar) Strong analytical thinking and problem-solving skills Excellent written and verbal communication abilities Self-motivated with ability to work independently and manage multiple projects Preferred Qualifications Experience with GitHub API, GraphQL, or other developer APIs Knowledge of software engineering concepts (code review processes, CI/CD, testing) Familiarity with cloud platforms (AWS, GCP, Azure) and big data tools Experience with statistical analysis and hypothesis testing Background in machine learning or predictive modeling Previous internship or project experience in data analytics or software development Interest in open-source software and development communities Technical Environment You'll work with: Languages: Python, SQL, R Tools: Jupyter notebooks, Git, GitHub API Application Requirements Please submit: Resume highlighting relevant coursework and projects Cover letter explaining your interest in data analytics and software development Portfolio or GitHub profile showcasing data analysis projects (required) Optional: Link to a project analyzing any public dataset Job Type: Full-time Pay: ₹5,000.00 - ₹10,000.00 per month Education: Bachelor's (Preferred)

Hiring R Developers for Pune,Hyderabad,Bangalore,Kolkata About the Company A global engineering, technology and consulting service provider, partnered with leading organizations to guide them through their business transformation, helping them achieve operational excellence and future-proof their businesses. About the Role As an R Developer, you will be responsible for developing and maintaining R packages, implementing statistical models, and performing data analysis to support business decisions. Responsibilities • Proven experience as an R Developer or in a similar role. • Strong proficiency in R programming language and RStudio. • Familiarity with machine learning libraries and frameworks in R (e.g., caret, randomForest, xgboost). • Solid understanding of statistical methods and data analysis techniques. • Experience with R packages development and maintenance. • Proficiency in data manipulation and transformation using dplyr, tidyr, data.table, and other relevant packages. • Knowledge of data visualization tools such as ggplot2. • Experience in implementing and validating complex statistical models Experience:7+ years Job location : Pune,Hyderabad,Bangalore,Kolkata To apply, please share your updated resume to laxmir@gkhrconsulting.com highlighting your expertise and experience in the above skills.

Key Responsibilities Collaborate with business stakeholders to identify opportunities for leveraging data and AI to drive business solutions in the insurance space. Design and implement forecasting models, predictive models, classification systems, and deep learning solutions tailored to insurance-specific use cases. Own the end-to-end delivery of data science projects - from data exploration and model development to validation, deployment, and monitoring. Work with large and complex insurance datasets to extract meaningful patterns and drive decisions. Apply advanced statistical techniques, machine learning algorithms, and deep learning architectures to solve real-world business problems. Collaborate with data engineers and DevOps teams to productionize ML models and scale solutions on cloud platforms like Azure or AWS. Maintain awareness of the latest AI/ML tools, techniques, and industry trends to keep solutions and skills market-relevant. Mentor junior team members and provide technical leadership where needed. Build dashboards and reports to visualize the performance of models using tools such as Power BI, Tableau, or other visualization platforms (if Skills & Competencies : Proven experience in delivering complex AI/ML projects within the insurance domain preferably life, general, or health insurance. Expert-level proficiency in R and Python, with hands-on experience in : Machine Learning : XGBoost, LightGBM, Random Forest, SVM, etc. Deep Learning : CNNs, RNNs, LSTMs, Transformers (using TensorFlow, PyTorch, or Keras). Statistical modeling & forecasting : ARIMA, Prophet, Exponential Smoothing, etc. Strong understanding of modeling concepts, feature engineering, hyperparameter tuning, model validation, and performance evaluation metrics. Experience with data manipulation and transformation using pandas, dplyr, SQL, etc. Familiarity with cloud platforms (Azure or AWS) and their respective ML/AI services (Azure ML, Sagemaker, etc. Good understanding of data engineering concepts data pipelines, ETL processes, and working with structured and unstructured data. Ability to articulate findings clearly to both technical and non-technical stakeholders. Strong problem-solving ability and attention to detail in a fast-paced, high-performance environment. Knowledge of data visualization tools such as Tableau, Power BI, or Plotly is a : Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. 5 - 10 years of relevant experience in data science roles, preferably in insurance or financial services. Certifications in Machine Learning, Deep Learning, or Cloud-based AI services (e.g., Microsoft Azure AI Engineer, AWS ML Specialty) are a plus (ref:hirist.tech)

Role: R Analytics Support Mode: Onsite (5 days) (Rotational shift 24*7) NO night shift Location: Mumbai Job Summary We are looking for an experienced R Analytics Lead to manage the day-to-day operations of our R-based analytics environment. The role focuses on monitoring the execution of existing R scripts, resolving failures through root cause analysis and data cleaning, supporting business teams with production data requests, and mentoring the R Ops team for better process efficiency and incident handling. Key Responsibilities: Monitor Production Jobs : Oversee successful execution of scheduled R scripts; monitor failures, investigate issues, and take corrective actions. Root Cause Analysis: Troubleshoot script failures and identify data or logic issues; perform necessary fixes and re-execute the process to ensure output delivery. Data Cleaning: Handle raw or inconsistent production data by applying proper cleaning techniques to ensure smooth script execution. Production Data Requests: Fulfill various production data and reporting requests raised by business stakeholders using R and SQL. Issue Resolution & Team Support: Act as the go-to person for any technical issues in the R Ops team. Guide and support team members in identifying problems and resolving them. Process Improvement: Identify areas to improve existing R code performance, suggest enhancements, and help automate or simplify routine tasks. Collaboration with Development & QA : Support testing, deployment, and monitoring activities for new script developments or changes in the production environment. Knowledge Sharing : Train and mentor team members on R coding standards, production support practices, database usage, and debugging techniques. Required Qualifications 6+ years of experience in analytics, with at least 4 years in a lead or senior operations/support role. Strong hands-on experience in R programming (especially with packages like dplyr, data.table, readr, lubridate). Proficiency in SQL for data extraction, transformation, and analysis. Experience in handling production support, script monitoring, and issue resolution. Demonstrated ability to lead teams, train junior members, and coordinate across departments. Desirable Skills Familiarity with scheduling tools and database connections in a production environment. Ability to document processes, communicate issues clearly, and interact with business users.

Job Summary We are looking for an experienced R Analytics Lead to manage the day-to-day operations of our R-based analytics environment. The role focuses on monitoring the execution of existing R scripts, resolving failures through root cause analysis and data cleaning, supporting business teams with production data requests, and mentoring the R Ops team for better process efficiency and incident handling. --- Key Responsibilities Monitor Production Jobs: Oversee successful execution of scheduled R scripts; monitor failures, investigate issues, and take corrective actions. Root Cause Analysis: Troubleshoot script failures and identify data or logic issues; perform necessary fixes and re-execute the process to ensure output delivery. Data Cleaning: Handle raw or inconsistent production data by applying proper cleaning techniques to ensure smooth script execution. Production Data Requests: Fulfill various production data and reporting requests raised by business stakeholders using R and SQL. Issue Resolution & Team Support: Act as the go-to person for any technical issues in the R Ops team. Guide and support team members in identifying problems and resolving them. Process Improvement: Identify areas to improve existing R code performance, suggest enhancements, and help automate or simplify routine tasks. Collaboration with Development & QA: Support testing, deployment, and monitoring activities for new script developments or changes in the production environment. Knowledge Sharing: Train and mentor team members on R coding standards, production support practices, database usage, and debugging techniques. Required Qualifications 6+ years of experience in analytics, with at least 4 years in a lead or senior operations/support role. Strong hands-on experience in R programming (especially with packages like dplyr, data.table, readr, lubridate). Proficiency in SQL for data extraction, transformation, and analysis. Experience in handling production support, script monitoring, and issue resolution. Demonstrated ability to lead teams, train junior members, and coordinate across departments. Desirable Skills Familiarity with scheduling tools and database connections in a production environment. Ability to document processes, communicate issues clearly, and interact with business users.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Associate Analyst, R Programmer-2 Overview The Mastercard Economics Institute (MEI) is an economics lab powering scale at Mastercard by owning economic thought leadership in support of Mastercard’s efforts to build a more inclusive and sustainable digital economy The Economics Institute was launched in 2020 to analyze economic trends through the lens of the consumer to deliver tailored and actionable insights on economic issues for customers, partners and policymakers The Institute is composed of a team of economists and data scientists that utilize & synthesize the anonymized and aggregated data from the Mastercard network together with public data to bring powerful insights to life, in the form of 1:1 presentation, global thought leadership, media participation, and commercial work through the company’s product suites About The Role We are looking for an R programmer to join Mastercard’s Economics Institute, reporting to the team lead for Economics Technology. An individual who will: create clear, compelling data visualisations that communicate economic insights to diverse audiences develop reusable R functions and packages to support analysis and automation create and format analytical content using R Markdown and/or Quarto design and build scalable Shiny apps develop interactive visualisations using JavaScript charting libraries (e.g. Plotly, Highcharts, D3.js) or front-end frameworks (e.g. React, Angular, Vue.js)work with databases and data platforms (eg. SQL, Hadoop) write clear, well-documented code that others can understand and maintain collaborate using Git for version control All About You proficient in R and the RStudio IDE proficient in R packages like dplyr for data cleaning, transformation, and aggregation familiarity with dependency management and documentation in R (e.g. roxygen2) familiar with version control concepts and tools (e.g. Git, GitHub, Bitbucket) for collaborative development experience writing SQL and working with relational databases creative and passionate about data, coding, and technology strong collaborator who can also work independently organized and able to prioritise work across multiple projects comfortable working with engineers, product owners, data scientists, economists Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Job Purpose; To evaluate and validate the quality, accuracy, and relevance of the data and analytics outputs, and ensure they adhere to the standards and best To stay updated with the latest trends and developments in the data and analytics field, and leverage them to improve the team's capabilities and performance To lead and mentor a team of data analysts and engineers, and foster a culture of learning, innovation, and collaboration within the team and across the organization Key Accountabilities Tag Management • Own channel wise mapping and click to visit sanity • Implement best practices in Tag Management Adobe Analytics Implementation • Define and own dimensions and metrics • Define channel rules and custom implementation as per business objectives • Own GA/AA versus DB variance in transactions and revenue • Installing, configuring, testing, and troubleshooting Adobe software products such as Adobe Experience Manager, Adobe Analytics, Adobe Target, and Adobe Campaign. • Providing technical guidance and best practices for Adobe software implementation and integration. • Creating and maintaining documentation and reports on Adobe software performance, issues, and solutions. A/B Testing & Personalization • Drive the overall conversion optimization and landing page optimization agenda • Co-own traffic to lead conversion with Product Attribution and MIS Automation • Manage the complexity of multiple truths (Adwords, DBM, Facebook, Google analytics, Internal CRM) and converge on a single truth • Automation of critical dashboards for decision making and business insights Channel mix modelling & Data driven attribution • Answer the ultimate questions. How much to spend in which channel? • Who to market, when to spend and which channel to use? • How to successfully move from campaign to audience marketing? Other Competencies • Apply advanced statistical and analytical techniques, such as machine learning, predictive modeling, and optimization, to generate insights and solutions for complex business problems and opportunities Technical Competencies (Preferred domain knowledge) SQL: Competency to write and execute complex queries, join multiple tables, create views and functions, and optimize the performance of your database. Python: Ability to use Python for data manipulation, processing, and modeling, as well as for creating web applications and APIs. You should also be proficient in using libraries such as pandas, numpy, scipy, sklearn, matplotlib, seaborn, and flask. R: Use R for statistical analysis, data visualization, and machine learning. You should also be familiar with popular packages such as tidyverse, ggplot2, dplyr, tidyr, caret, and shiny. Tableau: Ability to create interactive dashboards and reports using Tableau, as well as connect to various data sources and perform data blending and aggregation. Power BI: Competency to use Power BI for data visualization and business intelligence, as well as create and share reports and dashboards using Power BI Desktop and Power BI Service. Familiar with web services and APIs such as REST, SOAP, and OAuth. Skills/Qualities Required Strong analytical and critical thinking skills, with proficiency in data analysis tools and techniques Excellent communication skills, capable of translating complex data into clear, actionable insights for non-technical stakeholders Detail-oriented with strong organizational skills, able to manage multiple projects and meet deadlines Keen interest in staying updated with the latest trends in data analytics and e-commerce

As an integral part of the MC Analytics team, your role in Real-World Evidence (RWE) generation will be crucial in bridging the gap between clinical effectiveness and the commercial success of pharmaceutical brands. Collaboration between clinical and commercial disciplines is key at MC Analytics, where valuable insights are shared to guide decision-making. The importance of considering commercialization early in the drug development process is emphasized, and we are dedicated to partnering with you to create fully integrated RWE solutions tailored for the peri-approval phase, ensuring the collection of essential data for a successful product launch. By focusing on Real-World Evidence generation to meet the needs of key stakeholders, you will provide: - The necessary data to support regulatory approval and licensing processes. - The evidence required by physicians to confidently prescribe the drug. Your proficiency in coding will play a significant role in this role, including: - Advanced/Expertise in R programming with a focus on dplyr and tidyverse packages. - Skilled in managing complex datasets, handling missing values, and performing data pre-processing tasks efficiently. - Experience with version control systems such as GitHub and GitLab. - Advanced SQL skills to write optimized and scalable queries. - Ability to write modular and reusable code, emphasizing best practices and functions. The desired qualifications and skills for this role include: - A degree in Statistics/Data Science (B.Sc/M.Sc) with 1-2 years of experience in Real-world data or Oncology. - Proficiency in implementing statistical methods for descriptive statistics, Kaplan-Meier curves, visualization plots, etc. - Demonstrated ownership of deliverables, ensuring timely and high-quality outcomes. - Capability to work independently while proactively seeking guidance when needed. - Willingness to follow directions, accept oversight, and collaborate effectively in a team setting. - Adaptability to thrive in a cross-functional and highly collaborative work environment. Join us at MC Analytics and be a part of a dynamic team dedicated to delivering impactful Real-World Evidence solutions. Visit our website at https://mcanalytics.co.in/ to learn more about our work and culture.,

Title: Data Analyst Nature of position: 3-6 months consultancy contract, 20 hours/week Location: New Delhi Role overview: We are looking for a highly proficient Research Analyst with expertise in R programming to lead data analysis and visualization for public health nutrition research. The role involves working with large datasets and translating complex data into actionable, policy-relevant insights using R. Key Responsibilities: Perform data cleaning, transformation, and analysis using R Develop scripts and workflows for automated data processing and reporting Connect to external data sources, including: (SQL-based databases hosted on servers) Use R to conduct exploratory and inferential data analysis aligned with research objectives Document code, analysis steps, and data workflows for transparency and reuse Build and maintain data dashboards, visualizations, and summary reports using R packages (e.g., ggplot2, plotly) Ensure data quality, validation, and documentation throughout the analysis . Essential Qualifications and Skills: PhD in Data Science, Statistics, Public Health, Biostatistics Minimum 2–4 years of experience working in a data analyst or research analyst role Advanced proficiency in R programming, including data wrangling ( dplyr , tidyr ), visualization, and reporting Experience with connecting R to remote servers and databases (e.g., using DBI , RPostgres ) Experience working with health, nutrition, or development datasets preferred Strong understanding of data cleaning, wrangling, and quality assurance Desirable Skills: Prior experience in working with national or regional nutrition data and research in India Experience with Shiny apps, rmarkdown etc.

Description year Of exp- 6 to 10 Years Location- Noida, Pune, Bangalore, Nagpur Requirements Job Requirements: 6+ years of experience in a Data Scientist role Strong analytic skills related to working with unstructured datasets. Strong understanding of statistical methods and hypothesis testing. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. Experience supporting and working with cross-functional teams in a dynamic environment. Required Skills: Programming Languages: Proficiency in Python API / Framework: Hands-on experience with PySpark Data Manipulation: Strong experience with libraries like pandas, NumPy, dplyr, etc. Machine Learning: Hands-on experience with ML algorithms (regression, classification, clustering, etc.) Machine learning Models: Experience developing and tuning machine learning models such as Random Forest, Support Vector Machines (SVM), Natural Language Processing (NLP) techniques Cloud: Hands-on experience with AWS services for data science and ML, including S3 and EC2 Orchestration tool: Experience with orchestration tools like Luigi to manage data pipelines or ML workflows. Statistical Analysis: Solid foundation in probability, statistics, hypothesis testing, and experimental design (e.g., A/B testing). Data Visualization: Experience with visualization tools such Tableau, or Power BI. SQL & Databases: Ability to write complex SQL queries; familiarity with relational databases (PostgreSQL, MySQL, etc.). CICD: Experience with CI/CD practices and tools (GitHub) for automating data workflows and model deployments. Other Tool: Proficient in Microsoft Excel for exploratory data analysis, reporting, and data validation. Soft Skills: – Strong problem-solving and critical thinking abilities. – Excellent communication skills to explain technical concepts to non-technical stakeholders. – Ability to work independently and collaboratively in a fast-paced, agile environment. – Detail-oriented, with a focus on data quality and accuracy. Good To have: Domain Knowledge. Job responsibilities Collaborate with data engineers, analysts, and business stakeholders to understand requirements and deliver solutions. Monitor model performance and retrain as needed to ensure accuracy and reliability. Collect, clean, and preprocess large datasets from various sources. Develop statistical models and machine learning algorithms to solve business problems. Stay updated with the latest industry trends, tools, and technologies. What we offer Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally. Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today. Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way! High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do. About GlobalLogic GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Associate Analyst, R Programmer-2 Overview The Mastercard Economics Institute (MEI) is an economics lab powering scale at Mastercard by owning economic thought leadership in support of Mastercard’s efforts to build a more inclusive and sustainable digital economy The Economics Institute was launched in 2020 to analyze economic trends through the lens of the consumer to deliver tailored and actionable insights on economic issues for customers, partners and policymakers The Institute is composed of a team of economists and data scientists that utilize & synthesize the anonymized and aggregated data from the Mastercard network together with public data to bring powerful insights to life, in the form of 1:1 presentation, global thought leadership, media participation, and commercial work through the company’s product suites About The Role We are looking for an R programmer to join Mastercard’s Economics Institute, reporting to the team lead for Economics Technology. An individual who will: create clear, compelling data visualisations that communicate economic insights to diverse audiences develop reusable R functions and packages to support analysis and automation create and format analytical content using R Markdown and/or Quarto design and build scalable Shiny apps develop interactive visualisations using JavaScript charting libraries (e.g. Plotly, Highcharts, D3.js) or front-end frameworks (e.g. React, Angular, Vue.js)work with databases and data platforms (eg. SQL, Hadoop) write clear, well-documented code that others can understand and maintain collaborate using Git for version control All About You proficient in R and the RStudio IDE proficient in R packages like dplyr for data cleaning, transformation, and aggregation familiarity with dependency management and documentation in R (e.g. roxygen2) familiar with version control concepts and tools (e.g. Git, GitHub, Bitbucket) for collaborative development experience writing SQL and working with relational databases creative and passionate about data, coding, and technology strong collaborator who can also work independently organized and able to prioritise work across multiple projects comfortable working with engineers, product owners, data scientists, economists Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. R-250449