Data Scientist Off Grid Electric Arusha
Full-Time
30th May 2018
1674

Position
Off Grid 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.
Application

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