Role and responsibilities:
Leadership and Mentorship
Team Leadership :
Lead and mentor a team of Data Scientists and Analysts, guiding them in best practices, Advanced mthodologies, 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 mthodologies, 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.
- Proven experience of 5+ years in programming languages, machine learning, data visualization and statistical analysis.
