Predictive Analytics Scientist

Company Description ArborVitae helps businesses unlock the power of AI by combining intelligent solutions with specialized talent to build, deploy, and scale advanced technologies. The company partners with organizations on their AI transformation journey by identifying opportunities for automation, enabling AI-driven workflows, and supporting effective adoption of emerging technologies. ArborVitae addresses one of the biggest challenges in AI adoption by connecting companies with experts across AI Engineering, Data, SaaS, Product, and broader Technology domains. From AI enablement to building high-performing teams, ArborVitae empowers businesses to innovate, grow, and stay ahead in a rapidly evolving digital landscape.
Role Description The Predictive Analytics Scientist will design, develop, and validate predictive models and statistical analyses to support data-driven decision-making for ArborVitae’s clients. Day-to-day responsibilities include gathering and preparing data, exploring patterns and trends, building and testing machine learning and forecasting models, and translating analytical findings into clear, actionable insights. The role will collaborate closely with cross-functional stakeholders to understand business problems, define analytical approaches, and present results through dashboards, reports, and visualizations. This is a contract role based on-site in Noida, requiring regular engagement with internal teams and client partners to ensure models are aligned with business objectives and performance standards.
Qualifications
Strong foundation in statistics, probability, and predictive modeling, with experience in regression, classification, and time-series analysis.
Proficiency in analytics and programming tools such as Python or R, including relevant libraries for machine learning, data manipulation, and visualization.
Hands-on experience with data preparation, feature engineering, and working with structured and semi-structured datasets using SQL or similar query languages.
Ability to interpret complex analytical outputs and communicate insights clearly to non-technical stakeholders through reports, presentations, and data visualizations.
Familiarity with machine learning workflows, model evaluation, and deployment concepts in production or business environments.
Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative field.
Strong problem-solving skills, attention to detail, and the ability to work independently as well as collaboratively in an on-site team setting.
Experience in AI, automation, or digital transformation projects is a plus; exposure to client-facing or consulting environments is beneficial.

Work arrangement
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