Team Lead – Analytics & Data Science – LenDenClub

Job Description Job Role: Analytics & Data Science Team Lead

About LenDenClub:

LenDenClub stands as a leading peer-to-peer lending platform, offering an alternative investment avenue to investors seeking high returns and creditworthy borrowers in need of short-term personal loans. With over 8 million users and 2 million investors onboard, LenDenClub has emerged as a preferred platform, providing returns ranging from 10% to 12%. Investors benefit from a convenient medium to browse through numerous borrower profiles, outperforming traditional asset classes while being shielded from market volatility and inflation. LenDenClub has recently secured a Series A funding of US $10 million, valuing the company at over US $51 million, indicating significant growth potential.

Why Work at LenDenClub:

LenDenClub is recognized as a great place to work, certified by the globally renowned Great Place to Work Institute, Inc. Employees thrive in an environment of high trust and high-performance culture, fostering personal and professional growth. As a LenDenite, you join a dynamic team of individuals driven by passion and ownership, empowered to pursue their career aspirations without constraints.

Job Responsibilities:

  • Analyze extensive and intricate datasets to derive meaningful insights and trends.
  • Develop statistical models and algorithms to discern patterns and correlations in the data.
  • Interpret data findings and offer actionable recommendations to stakeholders.
  • Collaborate closely with business leaders to grasp objectives and challenges.
  • Formulate data-driven strategies to tackle business issues and streamline processes.
  • Engage with cross-functional teams to align analytics initiatives with overarching business objectives.
  • Produce clear and concise reports, dashboards, and visualizations.
  • Automate reporting procedures to ensure timely and accurate insights delivery.
  • Construct predictive models for forecasting future trends, customer behavior, and business outcomes.
  • Evaluate model performance, make necessary refinements, and iterate for enhanced accuracy.
  • Apply machine learning techniques to augment predictive analytics capabilities.
  • Ensure data accuracy, consistency, and reliability across various databases and sources.
  • Liaise with IT teams to optimize data storage, retrieval, and processing.
  • Keep abreast of the latest tools and technologies in data analytics.
  • Provide analytical support to marketing, credit, and product development teams.
  • Collaborate with data engineers and IT professionals to streamline data pipelines and integration.
  • Mentor junior analysts and offer guidance on analytics best practices.
  • Proficient in data analysis tools and languages such as SQL, R, Python, or similar.
  • Strong background in statistical analysis, predictive modeling, and machine learning techniques.
  • Experience with data visualization tools like Tableau, Power BI, or similar platforms.

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