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Key ResponsibilitiesData AnalysisAnalyze large datasets to identify trends, patterns, and insights.Develop and implement data cleaning and preprocessing techniques.Conduct exploratory data analysis to discover hidden patterns and correlations.Statistical ModelingBuild and deploy statistical/data science models to tackle business problems.Perform hypothesis testing and develop experiments to validate models.Work together with collaborators, customers, partners, and team members to grasp model requirements and objectives.Machine LearningDevelop and deploy machine learning algorithms for predictive modeling.Evaluate and fine-tune models for efficient performance.Stay updated on the latest advancements in machine learning and data science.Data VisualizationBuild visually captivating and insightful data visualizations.Share findings with both technical and non-technical collaborators.Use tools like Tableau, Power BI, or others for effective data representation.CollaborationWork closely with cross-functional teams, including business analysts, engineers, and other data professionals.Offer mentorship to junior data scientists and foster a collaborative work environment.Project ManagementHandle end-to-end data science projects, from problem definition to implementation.Prioritize tasks, meet deadlines, and ensure project deliverables align with business goals.Continuous LearningKeep updated with industry trends, new technologies, and standard processes in data science.Actively participate in professional development activities and training.QualificationsBachelor’s or equivalent experience in a relevant field (e.g., Computer Science, Statistics, Data Science).Demonstrable experience in data analysis, statistical modeling, and machine learning, with a minimum of 5+ years.Experience in developing a recommendation model will be a plus point.Proficiency in programming languages such as Python or R.Proficiency in working with cloud platforms such as Databricks, GCP, etc.Strong knowledge of data manipulation and analysis tools (e.g., Pandas, NumPy).Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch).Excellent communication and collaboration skills.Strong problem-solving and critical-thinking abilities.
