Chief Data Scientist-Full-Time

AML Monitor.

Data Analysis and Interpretation: Analyze large datasets to identify trends, patterns, and correlations, and translate findings into actionable insights.

Machine Learning Development: Develop and deploy machine learning models for predictive analysis, optimization, and other business applications.

Statistical Modeling: Design and implement statistical models to solve complex business problems and improve operational efficiency.

Data Visualization: Communicate findings effectively through data visualization techniques, such as charts, graphs, and dashboards.

Collaboration: Collaborate with cross-functional teams to understand business requirements, provide analytical support, and deliver solutions.

Quantitative Analysis: Utilize quantitative analysis, experimentation, data extraction, and data presentation to formulate strategies for various financial products.

Team Building: Collaborate with cross-functional and Product, Engineering, and engineering teams to support, advise, and implement product investment and strategy decisions.

Role Specific Technical Competencies

Master’s degree in Computer Science, Computing engineering, Mathematics, Finance, Commerce or a related field.

Advanced skills in Information Technology, certification or diploma in Information Technology.

3+ years of experience in Data Science

Data science experience ideally in ESG domain

Solid SQL skills for querying relational databases (e.g., SQL Server)

Functional Requirement:

Proficiency in producing concise, comprehensible code adhering to prevailing industry benchmarks and practices.

Comprehensive understanding of both theoretical and practical aspects of Machine Learning principles.

Capability to identify and address data biases, proposing and implementing suitable mitigation strategies.

Demonstrated adeptness in interpersonal communication, effectively articulating intricate technical concepts to non-technical audiences.

Openness to diverse viewpoints and perspectives, fostering an inclusive and collaborative work environment.