About the job

We are looking for a Senior Data Scientist who will proactively fetch data and information from various sources to support our product, sales, leadership, operations, and marketing teams with insights gained from analyzing company data.

The ideal candidate for the Senior Data Scientist position is adept at sifting through data points to create organized categories, comparing data points to current company processes, and writing reports outlining business predictions or proposals. You are great at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. You have proven ability to drive business results with your data-based insights through a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms, and creating/running simulations. And you are comfortable collaborating and communicating with a wide range of stakeholders and functional teams.

Non-Negotiables

• Our culture is summarized by our values; Doing the right thing, Having fun, Caring & Protecting, and also Having a low ego. We need a candidate who relates to these values
• 5+ years of experience manipulating data sets and building statistical models, with a current title as Senior Data Scientist or Lead Data Scientist.
• An individual is willing to push through the uncertainty of a newly formed data team. This person will find themselves setting up the building blocks of the data function and jumping in to work closely with software engineers
• Must be a Kenyan citizen or willing to translocate to Kenya

Responsibilities

• Working with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Developing and improving data collection procedures for use in analytic systems.
• Preprocessing, cleansing, and validating the integrity of structured and unstructured data for use in further analysis.
• Mining and analyzing usable data from company databases to facilitate optimization and improvements in product development, marketing, sales, and other business strategies.
• Assessing the effectiveness and accuracy of new data sources and data-gathering techniques.
• Developing custom data models and algorithms to apply to data sets.
• Using predictive modelling to increase and optimize customer experiences, fraud detection and other business outcomes.
• Coordinating with different functional teams to implement models and monitor outcomes.
• Developing processes and tools to monitor and analyze model performance and data accuracy.
• Analyzing large amounts of information to find patterns and solutions.
• Developing prediction systems and machine learning algorithms.
• Communicating and presenting findings in a clear manner.
• Proposing solutions and strategies to tackle business challenges.

Qualification

• 5+ years of experience manipulating data sets and building statistical models
• A degree in Statistics, Mathematics, Computer Science, or another quantitative field.
• A Master’s or Professional certification is an added advantage.
• Programming Skills – knowledge of and experience with Statistical programming languages like R, Python, SQL, Java, Scala, C++, or JavaScript
• Experience using web services: Redshift, S3, Spark, etc.
• Experience working with and creating data architectures
• Experience with different machine learning techniques and algorithms (clustering, regression, simulation, scenario analysis, modelling, decision tree learning, artificial neural networks, k-Nearest Neighbors, Naive Bayes, SVM, etc.) and their real-world advantages/drawbacks
• Experience in statistical and data mining techniques (text mining, GLM/Regression, Random Forest, social network analysis, Boosting, Trees, etc.)
• Experience visualizing and presenting data for use by stakeholders using Tableau, D3, matplotlib, ggplot, etc.
• Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies
• Excellent written and verbal communication skills for coordinating across teams and communicating findings to technical and non-technical teams
• Desire to learn and master new technology skills and techniques
• Strong problem-solving skills and aptitude
• An ability to navigate ambiguity

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