Data Scientist

Role and responsibilities: Leadership and Mentorship Team Leadership : Lead and mentor a team of Data Scientists and Analysts, guiding them in best practices, Advanced méthodologies, and carrer development. Project Management : Oversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous Learning : Stay at the forefront of industry trends, new technologies, and méthodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder Engagement : Work closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of Insights : Present complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive Models : Create and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative Research : Conduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis : Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance Metrics : Define and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit Analysis : Perform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm Development : Develop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and Simulation : Conduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. What we're looking for Advanced Statistical Techniques : Expertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AI : Proficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming Languages : Strong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management : Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data Visualization : Proficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud Computing : Familiarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative Analysis : Deep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic Trading : Experience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Requirements : A bachelor's degree in a related field, such as computer science, data science or statistics. Show more Show less