Senior Data Scientist

Summary

Join Nagarro, a global digital product engineering company, as a Senior Data Scientist to lead data-driven projects and drive strategic decisions. You will collaborate with a team of data professionals, building and deploying advanced statistical models and machine learning solutions. This role requires guiding the design, development, and deployment of machine learning models, leading end-to-end data science projects, and translating business challenges into data-driven solutions. You will communicate analytical findings to various stakeholders and foster a culture of continuous learning and innovation. The ideal candidate possesses strong Python and SQL skills, along with experience in statistical modeling, data engineering, and visualization. A Bachelor's or Master's degree in a related field and 5+ years of experience are required.

Requirements

• Python (Strong)
• SQL (Strong)
• Statistics
• Education: Bachelor’s or Master’s in Data Science, Computer Science, Statistics, or a related field
• Experience: 5+ years of experience in data science roles with proven project execution in statistical modeling, data engineering, and visualization

Responsibilities

• Guide the design, development, and deployment of machine learning models and statistical analyses
• Lead end-to-end data science projects from ideation to implementation
• Collaborate with cross-functional teams to translate business challenges into data-driven solutions
• Communicate analytical findings and model results clearly to technical and non-technical stakeholders
• Promote a culture of continuous learning, innovation, and data best practices across the organization

Preferred Qualifications

• PySpark, R, C++, JavaScript, SAS, Excel
• Knowledge of distributed computing tools (e.g., Hadoop, Hive, Kafka, MapReduce)
• Experience with ML techniques (e.g., GLM, regression, boosting, deep learning, CNN, RNN)
• Exposure to specialized ML areas like text analytics, image recognition, or graph analysis
• Familiarity with big data tools and cloud platforms (e.g., Apache Spark, Azure Data Lake, Azure ML, Databricks)
• Proficiency with data visualization tools (e.g., Power BI)
• Version control and collaboration tools (e.g., Git, Jupyter Notebooks)
• Strong understanding of AI and its business applications
• Ability to explain complex models and insights to diverse audiences
• Strong collaboration, storytelling, and presentation skills
• Willingness to learn new technologies and adapt quickly in a dynamic environment