Company Overview
Harnham specializes in Data and AI recruitment, staffing, and customized training solutions across diverse industry sectors. Operating throughout the UK, USA, and EU, we invite you to connect with us at info@harnham.com to discuss your specific needs.
Our dedicated recruitment and talent teams support every stage of the data and AI lifecycle—from data collection through to consumption—covering a broad range of roles and functions.
Whether you’re seeking permanent hires, contract professionals, specialized training programs, data-qualified graduates, or executive-level leadership, Harnham Group is fully equipped to meet all your data talent needs.
Responsibilities:
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Lead and mentor a team of data scientists responsible for developing and delivering advanced predictive models, risk assessment tools, and analytical solutions that generate significant business value.
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Architect, develop, and deploy sophisticated machine learning algorithms tailored for multiple business functions such as Underwriting, Marketing, and Operations to optimize performance and decision-making.
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Collaborate closely with cross-functional business partners and stakeholders to align data science initiatives with organizational objectives and support diverse teams and portfolio needs.
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Maintain clear and effective communication channels by presenting complex analytical findings to executive leadership, stakeholders, and team members, ensuring understanding and actionable insights.
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Process, manipulate, and analyze large and complex datasets using advanced technologies and tools including Python, Apache Spark, and Snowflake.
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Design, implement, and rigorously test machine learning models aimed at managing risk within acquisition channels, focusing on reducing credit and fraud losses while maximizing product profitability.
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Oversee the deployment and integration of scoring and predictive models onto decision platforms, including cloud-based environments, ensuring scalability and operational efficiency.
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Provide subject matter expertise on leveraging third-party data sources such as TransUnion and Experian, guiding effective data utilization to enhance risk strategies.
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Maintain thorough documentation of all models, methodologies, and processes utilizing tools like Jupyter Notebooks and RMarkdown to ensure transparency, reproducibility, and knowledge sharing.
Qualifications:
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A Master’s degree in a quantitative discipline such as Statistics, Economics, Mathematics, Engineering, or related fields; a Ph.D. is highly preferred.
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A minimum of six years of progressive experience in data science, risk modeling, or related analytical fields, with at least three years in a leadership or managerial capacity.
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Deep expertise in machine learning techniques including, but not limited to, Random Forest, Gradient Boosting, and LASSO regression.
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Strong proficiency in data engineering and manipulation, capable of handling complex data pipelines and architectures.
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Advanced programming skills in Python, R, Java, and familiarity with Linux environments.
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Experience working with big data technologies such as Apache Spark, Hadoop, and Snowflake.
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Knowledge of database technologies including NoSQL databases and expertise in parsing semi-structured data formats like JSON and XML.
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Excellent interpersonal and communication skills, with the ability to thrive in a dynamic, fast-paced environment and convey technical information to diverse audiences.