▷ [05/05/2024] Senior Manager Data Scientist
2 months ago
Biz2Credit was founded in 2007 with one goal; make business finance work better. We’re backed by Nexus Venture Partners and our 225,000 small business customers. Since we started, Biz2Credit has been the best place for small businesses to get funding online.
About Biz2x
Biz2X is the lending platform that has helped Biz2Credit become the premier online business lender. Biz2X is the platform chosen for business lending at banks and financial institutions around the world. Lenders choose our platform because they want to transform their lending practices digitally. Our approach is different because we know business lending. Biz2X is built on the insights and expertise that came from a decade-plus of Biz2Credit’s lending experience. That’s why the platform works so well for lenders of all sizes.
Introduction
Biz2Credit Talent Acquisition team is excited to accompany you on your recruitment journey with us. We aim to provide not only a smooth journey, but also one where we have the opportunity to adequately assess you as a candidate, whilst giving you something to take away; whatever the outcome. In this guide you will find useful information about our recruitment process and how to best prepare for your interviews. If you require any additional information, please reach out to your Talent Acquisition contact. They will be happy to assist you. Good luck
Learn More: & About Us:
- Senior Manager Data Science
This is a rare opportunity to join a fast-growing team, where you will play a major role in shaping Biz2X's future. We're looking for an exceptional candidate who is excited about the opportunity to build a next generation financial services business. We believe that there is a tremendous opportunity to leverage cutting-edge data science to inform smarter, faster decision making.
As a Biz2Credit leader in data science, you will shape the company's data-centric culture, work closely with our engineering team to develop our analytics infrastructure, and collaborate closely with our Chief Risk Officer on developing, validating, and automating our customer conversion and underwriting models. Hands on credit risk / modelling experience in a consumer/small business lending financial institute is a must.
Responsibilities
Team Leadership and Management
- Lead, mentor, and develop a team of data scientists, providing guidance and support for their professional growth and career advancement.- Foster a collaborative and inclusive team culture that encourages creativity, critical thinking, and continuous learning.- Define team goals, priorities, and performance metrics aligned with the company's strategic objectives.
Optimize Application Funnel
- Collaborate with product, marketing, and engineering teams to analyse and optimize the application funnel, leveraging data-driven insights to enhance user acquisition, conversion rates, and retention.- Utilize predictive modelling and machine learning techniques to identify factors influencing user behavior throughout the application process, enabling targeted interventions to improve the user experience and maximize conversion rates.- Implement A/B testing methodologies and experimentation frameworks to iteratively refine and optimize the application funnel, driving continuous improvement in key performance metrics such as conversion rates, customer lifetime value, and user engagement.- Monitor and analyze key metrics related to the application funnel, such as click-through rates, bounce rates, drop-off points, and conversion funnels, to identify areas for improvement and develop data-driven strategies to address them.- Collaborate with cross-functional teams to implement data-driven solutions, such as personalized user experiences, dynamic content optimization, and predictive lead scoring, to streamline the application process and enhance user engagement at each stage of the funnel.- Stay informed about industry best practices, emerging trends, and innovative technologies related to application funnel optimization, and proactively recommend new approaches and strategies to drive continuous improvement and competitive advantage.
Build and Maintain Credit Models
- Lead the development and maintenance of credit risk models, leveraging advanced statistical techniques and machine learning algorithms to assess and mitigate credit risk across various financial products and customer segments.- Collaborate with risk management and credit underwriting teams to define model requirements, gather relevant data sources, and validate model performance against established benchmarks and regulatory requirements.- Incorporate both traditional and alternative data sources, such as transactional data, behavioral data, and alternative credit data, to enhance the predictive power and robustness of credit risk models.- Monitor the performance of credit models over time, conduct regular model reviews, and testing, and conduct sensitivity analyses to ensure accuracy, stability, and alignment with business objectives.- Work closely with cross-functional teams to implement credit models into decision-making processes, such as loan origination, credit scoring, and portfolio management, and provide ongoing support and guidance to ensure effective model deployment and utilization.- Stay abreast of regulatory developments, industry trends, and best practices related to credit modeling and risk management, and proactively recommend enhancements and refinements to existing models to adapt to changing business environments and regulatory requirements.
Data Strategy and Governance
- Collaborate with cross-functional teams to define and implement data strategies that support business goals and drive innovation in the lending domain.- Establish and enforce data governance policies and best practices to ensure data quality, integrity, and compliance with regulatory requirements.
Advanced Analytics and Modeling
- Lead the design, development, and deployment of advanced analytics models and machine learning algorithms to extract actionable insights from large, complex datasets.- Apply statistical techniques and predictive modelling to identify trends, patterns, and correlations that drive business value and enhance customer experiences.
Product Development and Optimization
- Partner with product managers and engineers to integrate data science solutions into existing products and platforms, as well as to conceptualize and develop new data-driven products and features.- Continuously monitor and optimize the performance of data science algorithms and models to ensure scalability, efficiency, and accuracy.
Stakeholder Engagement and Communication
- Collaborate closely with key stakeholders, including executives, business leaders, and external partners, to understand business requirements, communicate insights, and influence decision-making.- Present findings, recommendations, and project updates in a clear and compelling manner through visualizations, reports, and presentations.
Qualifications:
- Master’s or Ph.D. degree in Computer Science, Statistics, Mathematics, Economics, or a related field.- 15+ years of experience in data science, machine learning, or artificial intelligence roles, preferably in the lending or financial services industry.- 7+ years of experience in a leadership or management position, with a proven track record of successfully leading and developing high-performing teams.- Proficiency in programming languages such as Python as well as in data manipulation and analysis tools (e.g., Pandas, NumPy, scikit-learn).- Strong understanding of statistical methods, machine learning algorithms, and data visualization techniques.- Expertise in NLP techniques and text analytics.- Familiarity with neural network architectures and deep learning frameworks (Pytorch)- Experience with big data technologies and platforms (e.g., AWS) is highly desirable.- Excellent communication skills, with the ability to translate complex technical concepts into business insights and recommendations.- Demonstrated ability to drive innovation, influence stakeholders, and deliver results in a fast-paced, dynamic environment
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