Data Science Lead - R01570348

Job requirements

Experience Range: 5 - 8 years of experience, including at least 5 years of hands-on work in data science, analytics, or related fields, with recent exposure to agentic AI solutions Key Responsibilities:

• Translate complex business challenges into structured data science problems, ensuring alignment with organizational objectives and measurable outcomes
• Develop, monitor, and validate OKRs using advanced statistical techniques to deliver actionable insights and track progress
• Execute advanced data wrangling, cleansing, and transformation on large, complex datasets to enable robust modeling and analysis
• Deliver impactful data-driven insights through clear data storytelling, utilizing visualization tools to communicate findings effectively to stakeholders
• Apply design thinking methodologies to create innovative analytical solutions and continuously optimize data science workflows and processes
• Lead technical decision-making for modeling iterations, optimizing model performance, and balancing computational efficiency with business requirements
• Collaborate with cross-functional teams, including engineering and product, to implement scalable data science solutions that drive business value
• Promote data literacy and foster a culture of data-driven decision-making by sharing best practices and industry trends across the organization

• Advanced proficiency in Python or R for data wrangling, preprocessing, and statistical analysis
• Expertise in statistical modeling and validation of performance metrics
• Experience with data visualization tools such as Tableau, Power BI, or Matplotlib
• Hands-on experience with machine learning algorithms and evaluation metrics
• Strong background in feature engineering and data mining
• Familiarity with big data technologies such as Spark or Hadoop
• Experience with cloud-based data platforms including AWS, Azure, or Google Cloud
• Knowledge of MLOps practices and deployment pipelines

• Experience with deep learning frameworks such as TensorFlow or PyTorch
• Exposure to agentic AI and rapid domain adaptation
• Experience with automation tools and scripting for data workflows

• Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline
• Certification in Data Science or Machine Learning from a recognized institution, such as Microsoft Certified: Azure Data Scientist Associate or IBM Data Science Professional Certificate
• Relevant coursework or certification in statistical analysis or business analytics