Data Scientist- R Programming

As an on-site Data Scientist (R) at our fast-growing IT consulting and analytics services firm, your role will involve leading model development, deployment, and stakeholder delivery for our enterprise clients in finance, retail, and healthcare sectors. Your responsibilities will include: - Designing and implementing end-to-end analytical solutions using R, including data preparation, feature engineering, model development, evaluation, and deployment. - Developing and validating statistical and machine-learning models (regression, classification, time-series, survival analysis) to solve business problems and improve KPIs. - Building interactive analytics and dashboards using R Shiny and ggplot2 to facilitate data-driven decision-making for business stakeholders. - Productionizing models and reproducible workflows using containerization (Docker), version control (Git), and CI/CD best practices. - Collaborating with data engineering and product teams to integrate models into pipelines and APIs, ensuring data quality, monitoring, and model retraining strategies. - Translating stakeholder requirements into analytical scopes, communicating results clearly, and providing recommendations based on rigorous statistical evidence. Skills & Qualifications Must-Have: - R - SQL - Machine Learning - Statistical Modeling - Data Visualization - R Shiny - Git - Docker Preferred Skills: - Python - Spark - AWS Qualifications: - 4+ years of professional experience in data science or analytics with primary hands-on use of R. - Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, or related quantitative field. - Proven track record of delivering production-ready models and business-facing dashboards in an on-site, client-engagement environment. - Strong problem-solving and stakeholder-management capabilities; ability to translate business needs into data-driven solutions. In addition to the technical aspects of the role, you will have the opportunity to work on high-impact, client-facing analytics projects spanning multiple industries. Our collaborative, mentorship-led environment emphasizes technical excellence and career growth, offering exposure to end-to-end product delivery and production ML engineering practices. As an on-site Data Scientist (R) at our fast-growing IT consulting and analytics services firm, your role will involve leading model development, deployment, and stakeholder delivery for our enterprise clients in finance, retail, and healthcare sectors. Your responsibilities will include: - Designing and implementing end-to-end analytical solutions using R, including data preparation, feature engineering, model development, evaluation, and deployment. - Developing and validating statistical and machine-learning models (regression, classification, time-series, survival analysis) to solve business problems and improve KPIs. - Building interactive analytics and dashboards using R Shiny and ggplot2 to facilitate data-driven decision-making for business stakeholders. - Productionizing models and reproducible workflows using containerization (Docker), version control (Git), and CI/CD best practices. - Collaborating with data engineering and product teams to integrate models into pipelines and APIs, ensuring data quality, monitoring, and model retraining strategies. - Translating stakeholder requirements into analytical scopes, communicating results clearly, and providing recommendations based on rigorous statistical evidence. Skills & Qualifications Must-Have: - R - SQL - Machine Learning - Statistical Modeling - Data Visualization - R Shiny - Git - Docker Preferred Skills: - Python - Spark - AWS Qualifications: - 4+ years of professional experience in data science or analytics with primary hands-on use of R. - Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, or related quantitative field. - Proven track record of delivering production-ready models and business-facing dashboards in an on-site, client-engagement environment. - Strong problem-solving and stakeholder-management capabilities; ability to translate business needs into data-driven solutions. In addition to the technical aspects of the role, you will have the opportunity to work on high-impact, client-facing analytics projects spanning multiple industries. Our collaborative, mentorship-led environment emphasizes technical excellence and career growth, offering exposure to end-to-end product delivery and production ML engineering practices.