Job overview:the data scientist will analyze and interpret complex data sets, develop predictive models, provide actionable insights, and enable data-driven decisions across the organization. The role involves applying advanced statistical analysis, machine learning techniques, and data visualization skills to support strategic business objectives.key responsibilities:data analysis & interpretation:extract, clean, and analyze large-scale structured and unstructured datasets.perform exploratory data analysis (eda) to discover insights, identify patterns, and recommend solutions.model development & deployment:develop, test, and deploy robust predictive models using machine learning, deep learning, and statistical techniques.continuously optimize and validate model performance and accuracy.visualization & reporting:develop intuitive visualizations, dashboards, and reports to effectively communicate insights to stakeholders.clearly articulate findings and recommendations to both technical and non-technical audiences.collaboration & communication:collaborate cross-functionally with data engineers, business analysts, and stakeholders to understand requirements and deliver solutions.document methodologies, processes, and findings comprehensively.innovation & improvement:remain current with emerging trends, technologies, and methodologies in data science and machine learning.proactively identify opportunities for process improvement and efficiency enhancements.required skills & qualifications:technical skills:strong proficiency in python (required, minimum 3 years), sql, and optionally r.experience with data manipulation and modelling frameworks (pandas, numpy, scikit-learn, tensorflow, pytorch).familiarity with data visualization tools such as tableau, power bi, matplotlib, and seaborn.experience with cloud data platforms, particularly snowflake (preferred).familiarity with data integration tools, particularly talend (preferred).analytical & problem-solving:advanced statistical knowledge, including regression, hypothesis testing, predictive modelling, and machine learning.excellent analytical thinking, problem-solving, and troubleshooting abilities.communication & collaboration:strong communication skills, able to present complex technical topics clearly to diverse audiences.proven ability to collaborate effectively within cross-functional teams.preferred qualifications:experience with nlp, computer vision, and advanced deep learning techniques.experience working in agile environments, with version control (e.g., git).demonstrated experience with business intelligence workflows and tools.expected outcomes:improved organizational decision-making capabilities through actionable insights.enhanced operational efficiency and business outcomes through predictive modelling and automation.significant contributions toward building robust analytics and data science capabilities within the organization.