Data Scientist

R ole: Data ScientistLocation: Remote, however travel might be required as per business requirementsWhere you're headedYou'll creatively use data to solve business challenges, often uncovering new and transformative opportunities along the way. Applying advanced analytics, quantitative tools, and modeling techniques, you'll interpret and offer recommendations based on insights from the data.Where you've beenYou're a problem solver, data expert, analyst, and communicator, who can create new algorithms from scratch. You have an advanced degree in a quantitative field, such as computer science, engineering, physics, statistics or applied mathematics, and have:Job Description:Familiarity with statistical techniques, data mining, hypothesis testing, and exploratory data analysisStrong knowledge of programming languages with a focus on machine learning and advanced analytics (such as Python, R, Scala)Experience working with large datasets, data pipelines, and relational databasesA collaborative mindset with the ability to communicate complex analytical concepts effectively to both technical and non technical stakeholdersExcellent problem solving skills with the ability to analyze issues, identify root causes, and recommend solutions quicklyProven experience building, validating, and deploying machine learning models end to end in production environmentsStrong understanding of model performance evaluation, experiment design, and model lifecycle managementAbility to translate business problems into analytical frameworks and measurable success metricsExperience working cross functionally with engineering, product, and business teams to deliver impact at scaleGood to Have:Experience with Generative AI, including large language models (LLMs), prompt engineering, fine tuning, and retrieval augmented generation (RAG)Exposure to Agentic AI concepts, such as autonomous agents, tool usage, planning, memory, and multi agent workflowsFamiliarity with modern ML/AI frameworks (e.g., PyTorch, TensorFlow) and MLOps tools for deployment and monitoringExperience deploying AI solutions on cloud platforms (Azure, AWS, or GCP) with an understanding of scalability and cost considerationsKnowledge of responsible AI practices, including model explainability, bias mitigation, and governance