• VP Data Science at Greenlight Planet, Inc.

  • Posted on: 12 July, 2018 Deadline: Not Specified
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    Greenlight Planet is a social, for-profit business that designs, distributes, and finances solar-powered home energy systems, for an underserved population: the 1.3 billion global consumers who don’t have access to an electrical grid, or find it too expensive for their needs. Founded in 2009, the company is a leader in the off-grid solar energy industry, serving over 30 million rural consumers in more than sixty countries, and growing fast. The company operates eleven offices throughout sub-Saharan Africa and South Asia, employs over 900 dedicated staff, works with dozens of major distribution partners (including many of the world’s largest microfinance institutions and retailers), and manages a network of 3,000 sales agents to directly reach end consumers.

    VP Data Science


    Job description

    This is an incredible opportunity for a mission-driven data guru who seeks a purposeful, long-term career benefiting the lives of over a billion underserved consumers in Sub-Saharan Africa and Asia: Come lead the data science team for one of the world’s most innovative, life-changing, growth-stage companies, expanding solar energy access and financial inclusion in exciting emerging markets!

    Greenlight currently employs data scientists, data analysts, and app developers within multiple internal teams, as well as external service providers. The company seeks to hire a senior technologist with excellent quantitative and technical skills to lead and mentor a centralized, world-class data science department. The key outputs of the department will include risk analysis and loan underwriting for lean-file consumers, sales-force and sales-process optimization, product design improvement through analysis of IoT-derived usage and behavioral data, and overall business intelligence.

    The VP of Data Science will be a hands-on technology leader, growing and mentoring a team, while retaining a lean, entrepreneurial approach. She or he will work with culturally diverse internal and external teams across the world, and should be comfortable working in a less rigid, more entrepreneurial, more geographically diverse, growth-stage company.

    Key responsibilities

    • Data Strategy & Operations
    • Determines the data strategy and operating model for the growing organization, which will include dramatic expansion of the company’s efforts in:
    • Data aggregation strategy (via, for example, Greenlight’s GSM cloud-connected energy systems, mobile apps handled by Greenlight field agents, Greenlight customer support call centers, SMS surveys, data partnerships with other companies/organizations touching the same consumers)
    • Data engineering, including architecture and technology
    • Data science and analytics, including traditional models and machine learning / artificial-intelligence approaches, for multiple purposes across the company.
    • Priority areas ripe for innovation include:
    • Credit risk prediction and analysis
    • Loan underwriting for lean-file consumers
    • Customer portfolio segmentation to inform pricing and opportunities for cross-sale
    • Sales force and sales process optimization
    • Product design improvement through analysis of IoT-derived usage and behavioral data
    • General business intelligence
    • Utilizes data insights to drive innovation – new products, systems, business initiatives
    • Vets and selects third-party software providers for core banking, CRM, and ERP systems, that feed data to the business (or, if third-party software is not well suited to the purpose, develops in-house solutions to needs currently addressed by third-party software).
    • Leadership and management
    • Assess talents and capabilities of existing data scientists, programmers, and analysts, how to leverage these, and how to build out the team with new hires over time.
    • Build the business’s data talent needs through role definition, recruitment, and development of a team who will jointly move the business’s agenda forward.
    • Provide leadership and guidance to the data team.

    Skills and experience

    • First and foremost, strong quantitative, statistical, and computer science aptitude
    • Expertise in SQL (AWS Redshift or Postgres preferred)
    • Expertise in statistical analysis and predictive modelling in modern languages (Python, R, or similar)
    • Orientation towards cloud-based data engineering (AWS preferred, either direct experience or experience overseeing specialists in this area)
    • Orientation towards machine learning and artificial intelligence approaches (either direct expertise or experience overseeing specialists in this area)
    • Proficiency with modern off-the-shelf BI / data analytical tools (Preferred: Looker)
    • Proven track record building innovative and successful data products, including demonstrated
    • Ability to perform advanced feature engineering
    • Ability to utilize both linear and non-linear models, as optimal for a given problem / product maturity / datasets
    • Ability to utilize both traditional and non-traditional data sources for predictive analytics
    • At least five years in senior data roles, including people management experience
    • Orientation towards credit risk analytics and loan underwriting / credit check processes, preferably in a fintech or consumer lending environment (ideally not a big traditional bank, unless in an innovation hub or similar)
    • Experience managing, mentoring, and retaining a nimble, lean data team

    Personal attributes

    • Excellent communication skills
    • Good commercial acumen, to derive commercially meaningful insights
    • Strategic and conceptual thinker with ability to translate strategy into plans and deliverables
    • Preference to collaborate across departments and cultures
    • Resilient, agile and flexible
    • Cost-conscious, with the ability to work in an entrepreneurial environment

    Method of Application

    Interested and qualified? Go to Greenlight Planet career website on www.linkedin.com to apply

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