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 outcomesDevelop, monitor, and validate OKRs using advanced statistical techniques to deliver actionable insights and track progressExecute advanced data wrangling, cleansing, and transformation on large, complex datasets to enable robust modeling and analysisDeliver impactful data-driven insights through clear data storytelling, utilizing visualization tools to communicate findings effectively to stakeholdersApply design thinking methodologies to create innovative analytical solutions and continuously optimize data science workflows and processesLead technical decision-making for modeling iterations, optimizing model performance, and balancing computational efficiency with business requirementsCollaborate with cross-functional teams, including engineering and product, to implement scalable data science solutions that drive business valuePromote data literacy and foster a culture of data-driven decision-making by sharing best practices and industry trends across the organizationRequired Skills:
Advanced proficiency in Python or R for data wrangling, preprocessing, and statistical analysisExpertise in statistical modeling and validation of performance metricsExperience with data visualization tools such as Tableau, Power BI, or MatplotlibHands-on experience with machine learning algorithms and evaluation metricsStrong background in feature engineering and data miningFamiliarity with big data technologies such as Spark or HadoopExperience with cloud-based data platforms including AWS, Azure, or Google CloudKnowledge of MLOps practices and deployment pipelinesPreferred Skills:
Experience with deep learning frameworks such as TensorFlow or PyTorchExposure to agentic AI and rapid domain adaptationExperience with automation tools and scripting for data workflowsDesired Qualifications:
Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related disciplineCertification in Data Science or Machine Learning from a recognized institution, such as Microsoft Certified: Azure Data Scientist Associate or IBM Data Science Professional CertificateRelevant coursework or certification in statistical analysis or business analytics
