Lead Data Scientist

Company Description NUCURV is a performance-driven organization built on the principles of building, transforming, and delivering measurable results. The company focuses on turning complex data and business challenges into practical, high-impact solutions. NUCURV values innovation, analytical rigor, and continuous improvement across its projects and services. Team members are encouraged to collaborate, experiment, and drive change that leads to sustainable performance gains. This environment offers professionals the opportunity to work on meaningful problems with real-world impact.

Role Description This is a project contract role for a Lead Data Scientist based in NCR. The Lead Data Scientist will design, develop, and deploy data science solutions that address complex business challenges, from problem framing through model implementation. Day-to-day responsibilities include leading end-to-end data science projects, managing data pipelines, performing exploratory data analysis, building and validating statistical and machine learning models, and translating insights into clear recommendations for stakeholders. The role involves mentoring data team members, establishing best practices in modeling and experimentation, and collaborating closely with cross-functional partners such as engineering, product, and operations. The Lead Data Scientist will also be responsible for communicating findings through compelling data visualizations and presentations, and for ensuring that models are monitored, maintained, and continuously improved in production environments.

Qualifications

• Strong foundation in Data Science and Data Analytics, with experience leading end-to-end analytical or machine learning projects.
• Proficiency in Statistics and Data Analysis for experimental design, hypothesis testing, and model evaluation.
• Hands-on experience with Data Visualization tools and techniques to communicate insights to technical and non-technical audiences.
• Advanced skills in programming languages commonly used in data science (e.g., Python or R) and familiarity with SQL and data manipulation.
• Experience working with large datasets, data pipelines, and relevant frameworks or platforms (e.g., pandas, scikit-learn, Spark, cloud environments).
• Proven ability to lead and mentor data professionals, set technical direction, and collaborate with cross-functional stakeholders.
• Excellent problem-solving, critical-thinking, and communication skills, with the ability to translate business questions into analytical approaches.
• Bachelor's or Master's degree in a quantitative field such as Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related discipline, or equivalent practical experience.
• Experience in deploying models to production and monitoring performance is highly beneficial.
• Familiarity with MLOps practices, version control, and reproducible research is a plus.