Data Scientist Job Arusha at Zola Electric (former Off Grid Electric)

AJIRALEO

Data Scientist Job Arusha at Zola Electric (former Off Grid Electric) | Deadline: 5th October, 2018
NAFASI ZA KAZI / AJIRA TANZANIA

Location: Arusha
Job Title: Data Scientist
Application Deadline: 2018-10-05

Company Description: Uncover hidden opportunities to make a global impact. Zola Electric (former Off Grid Electric) is a growth-stage start up that’s on track to light a million homes in Africa over the next couple of years with clean, affordable solar energy. At the heart of our business is innovative solutions that delight our customers. We are looking for a Director Logistics and Manufacturing to support our growth strategy in Africa, changing the lives of millions with our innovative products.

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This may be your dream job if you’re someone who dreams of combining your knowledge and skills enabling Zola Electric to change the renewable energy landscape. You’ll also need to be passionate about bringing solar energy to off-grid and other underserved markets (billions of people around the world) with the unique social, technical, and business challenges that come along with it. You are inspired by the opportunity to unleash whole continents of human potential, and motivated to help build a truly epic business.

Zola Electric, through its consumer brand Zola, combines Silicon Valley technology with local expertise to offer African homes and businesses a long-term solar solution to an unreliable grid. Adaptable to both energy needs and income, Zola Electric’s solution can be bought over time through a leasing structure. The first few watts starts a chain reaction that enables people to achieve commonly held aspirations: security, education, access to information, and a longer and more efficient day.

Today, Zola Electric powers more than 100,000 homes and businesses across Tanzania, Rwanda and Côte d’Ivoire. Zola Electric’s investors include: Tesla, Vulcan Capital, DBL Partners, The Packard Foundation, Helios Investment Partners, and responsibility. Zola Electric is the recipient of the 2016 UN Momentum for Change Award, Zayed Future Energy Prize, and the 2015 Global Cleantech 100. For more information, visit www.zolaelectric.com

Position

Zola Electric is seeking an experienced Data Scientist, who will establish the patterns and methods of leveraging very large data sets to build better tools, and design analytics to inform how the organization approaches its mission. With a holistic understanding of our customers and business, the data scientist works to ensure we have clean, meaningful data, and then help us rapidly understand and use the resulting insights inside our product and operations through machine learning techniques. Responsibilities for this position includes:

Create methods for acquiring sufficient quantity and accuracy of data, needed to produce meaningful insights in key areas of business
Write and maintain general guidelines to be used by engineering and operations in the collection of data
Define specifications for data collection, around specific features and business processes
Create quality controls/auditing measures to ensure trustworthiness of the data collected
Design data feedback loops within products to promote data collection
Acquire third-party public or commercial datasets to enhance our analytical reach
Collaborate with technical and business stakeholders to identify key questions to answer
Iterate on analytical models to identify predictive markers
Conduct big data explorations
Train peer analysts in advanced analytics techniques
Design and help build machine learning into our platform and related products
Find creative ways to generate value from existing data
Conduct research into new technologies, algorithms and techniques
Lead the development of a product from prototype through to production
Develop novel machine learning techniques
Lead internal programs to spread understanding of uses and methods of data
Work with software practice to embed data streams and machine learning into features
Collaborate with project leaders to orient work around data thinking
Define and maintain measures of company-wide adherence to data processes

Requirements

Educational, technical and analytical skills:

BS Computer Science, Engineering, Mathematics & Statistics or Advanced Science (or equivalent work background) is essential. MS or other advanced studies/certification in data science or related disciplines is an added advantage.
3+ years of professional or academic data science experience, with demonstrated expertise in statistics, machine learning, data visualization and other relevant fields
Mastery of SQL, Python and R and/or relevant programming languages/tools
Advanced knowledge of Apache Hadoop, Apache Hive and Apache Pig
Knowledge of ETL, analytics and big data tools such as Luigi, Looker, Apache Storm, Spark, and/or related tools
Knowledge of MATLAB and Scikit-learn or similar
Familiarity with Amazon AWS services like AWS Lambda and AWS Redshift
Knowledge of microservice architecture
Familiarity working with unstructured data sources
Expertise in creating hypotheses, using a methodological approach, quantifying the results, and obtaining actionable insights
Strong business acumen and problem-solving skills
Experience in processing real-time data in production
Machine learning skills

Competencies:

Ability to work unsupervised and communicate effectively across organizational boundaries
Knowledge of financial principles and strategic planning skills
Customer focused attitude with sufficient relationship management skills
Effective communicational and strong interpersonal/people management skills
Highly organized with effective time management skills
Not hesitant to challenge the status quo and to be innovative in technical as well as business domains

Other information
-The opportunity to directly improve millions of lives. By bringing sustainable electricity to a part of the world where 90% of people have no grid access.
-Few other activities can provide as fundamental impact to human lives as this.
-Some of the smartest, most committed, and hardest working co-workers in a distributed environment.

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