data scientist

Bachelor's or Master's degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Physics, or EngineeringKnowledge of the AI/ML lifecycle management and tools including EDA, Modelling, Integration/Deployment, Data/Model drift detection, Model retraining, etc.Familiarity with core techniques in statistical and machine learning e.g. regularized regression, time series analysis, decision trees, boosting algorithms, neural networks, clustering, and collaborative filtering.Experience working with structured, semi-structured, and unstructured data sourcesKnowledge in web crawling, natural language processing, and visualizationFamiliar with collaborative solutions, model & code versioning (Github), solution packaging (Docker), model deployment (Dataiku)Proficient in programming languages such as Python, R, and SQL (for data manipulation, cleaning, and analysis), Tableau, PowerBI or Spotfire,NumPy, Pandas, and Matplotlib for visualization.Ability to define problems, generate hypotheses, develop and test solutions, and effectively communicate complex technical concepts to non-technical stakeholders is essential for data scientists,Attention to detailAbility to collaborate effectively with others to achieve project goals. JOB DESCRIPTION Collect and extract large sets of structured and unstructured data from various sources such as databases, APIs, and web scraping.Clean and preprocess data to remove any inconsistencies, missing values, or errors to ensure the accuracy and reliability of the data.Use statistical, machine learning or deep learning techniques to analyze and model data to identify trends, patterns, and relationships to provide actionable insights.Use data visualization tools to create charts, graphs, and dashboards to communicate insights to stakeholders in a clear and concise manner.Develop predictive models using machine learning algorithms to forecast trends and future outcomes.Deploy models and systems developed, monitor and maintain them to ensure they are working effectivelyDocument their processes and methodologies to ensure that their work is reproducible and can be audited.Work with cross-functional teams such as product managers, software engineers, and business analysts to identify business problems and develop solutions.Explain complex technical concepts to non-technical stakeholders in a clear and concise manner.