Independently lead the development of machine learning models, owning feature engineering, extraction, model selection, and optimization  Design experiments by formulating statistical hypotheses, defining data requirements, pre-processing and cleaning the data, and performing the hypothesis testing. Operationalise models at scale applying AI and engineering best practices by working with the ML engineers. Experiment with various algorithms and techniques to advance model performance. Define feedback and evaluation methods for the business problems. Demonstrate excellent coding and debugging skills.

Make impactful contributions by leveraging AI and Machine Learning expertise to address pressing business challenges. Collaborate with cross functional teams to understand the business requirements and data architecture. Translate business requirements into technical solutions by working with the business and senior data scientists. Identify and document the data requirements and manage data collection and preparation for projects. Design and document training and testing strategy. Document methodologies, findings, and outcomes of model experiments and present it to the team and key stakeholders. Mentorship and Collaboration: Mentor junior team members, providing technical support, guidance on model development, and best practices implementation. Coach junior team members, helping them understand complex datasets, models, and business requirements by giving clear and actionable feedback. Encourage the development of best practices and innovative approaches in data analysis and modeling. Qualifications:  4+ years of experience as a data scientist involved in data extraction, analysis, and modeling. 4+ years of experience in Python and SQL or related tools for machine learning. Understanding of statistics and linear algebra. Proficiency in machine learning algorithms and all stages of machine learning. Familiarity with neural networks and deep learning. Basic knowledge about AWS services and cloud databases. Proficiency in handling structured and unstructured data. You would be successful in this role if you describe yourself as: