data scientist
6 the last 264 days, recently 2023-07-17
Responsibility
- develop and implement the overall credit risk and debt management strategy aligned with the company's goals and regulatory requirements
- create and maintain geospatial databases and help the business visualise the data
- extract geographic data from imagery, photography and data reconnaissance
Show more +7 - conduct regular reviews of credit risk and debt performance metrics, identify areas for improvement, and implement action plans to optimize outcomes
- create and collect geographic data and compile it into maps
- focus on the special characteristics of spatial data, using machine learning techniques to know where and why things happen
- foster a continuous learning and development culture within the credit and debt management team, promoting knowledge-sharing and skill-building initiatives
- monitor market trends and industry best practices in credit risk and debt management to ensure the organization remains at the forefront of innovative strategies
- work closely with the Data Science team to enhance and refine credit risk models, utilizing machine learning techniques to improve accuracy and predictive capabilities
- develop and deliver training programs for employees across the organization to promote credit and debt awareness and ensure a consistent understanding of credit risk management principles
Requirements
- proven track record of developing and implementing successful credit risk and debt management strategies
- advanced proficiency in statistical analysis and data manipulation, with hands-on experience using SQL. Knowledge of Python is highly beneficial
- experience analysing data and compiling in to maps
Show more +14 - strong leadership and team management skills, with the ability to inspire and motivate team members to achieve their full potential
- experience delivering data science projects in a non-academic setting
- ability to tag, layer and label datasets
- excellent problem-solving abilities and a proactive approach to identifying and addressing credit risk issues
- understanding of the full model life-cycle and defining key parameters. Creation, deployment, productionise and maintain
- be the technical interface between the data science team and the business stakeholders ensuring both parties are aligned and meeting expectations
- machine learning capabilities e.g Regression, Decision Trees, Random Forests, K-means, Neural Nets etc
- experience developing Machine Learning algorithms
- exceptional communication skills, both technical and non-technical, with the ability to present complex ideas clearly and concisely to various stakeholders
- strong programming skills ideally within Python
- strong programming
- strong programming in Python
- knowledge of GIS tools such as Other key tools include Geopandas, QGIS, PostGIS, CARTOframes
- have been involved as a senior member of a team or technical lead where you have provided subject matter expertise ideally across machine learning
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