As a Data Scientist, you will be identifying opportunities for data exploitation through in depth conversations with business stakeholders which includes:
- Understand the evolving problems and strategize about what data and techniques would be needed to solve it
- Develop different machine learning models, track their effectiveness, and deploy the most appropriate solution
- Build and operate production systems together with engineers to serve these solutions
- Present findings, solicit feedback and prioritise refinements to the analysis in close iteration with stakeholders while managing overall project timeline
Requirements
- A Bachelor's Degree or higher in Data Science, Computer Science, Statistics, Economics, Quantitative Social Science, or related disciplines. We will also factor in relevant certifications
- Capable of translating business use cases into analytical problems, and identifying appropriate data sources to tackle these problems.
- Proficient in writing scripts for data preparation and analysis, using modern analysis tools & programming methodologies.
- Proficient cleaning, imputing and correcting anomalies in the collected structured or unstructured data to ensure a high standard of quality in data sets to be used in the analysis work.
- Proficient in exploring and analysing datasets, applying probability and statistical methodologies and techniques to discover insights from the data.
- Proficient in building machine learning models to identify, recognise patterns and make predictions.
- Proficient in design principles and use of visualisations to best convey the intended information.
- Capable of developing data visualisation from standalone graphs and charts on to highly customised tools and apps while tightly integrated to the data systems for real time visualisation of information.
- Capable of translating results from analysis work into actionable recommendations for stakeholders.
- Capable of communicating results from analysis work in a coherent data story for stakeholders.
Technical Requisites:
- Deep understanding of system design, data structure and algorithms, data modelling, data access, and data storage.
- Proficiency in writing SQL for databases such as Postgres, MSSQL.
- Demonstrated ability in using cloud technologies such as AWS, Azure, and Google Cloud.
- Experience with orchestration frameworks such as Airflow, Azure Data Factory.
- Experience with distributed data technologies such as Spark, Hadoop.
- Proficiency in programming languages such as Python, Java, or Scala.
- Familiarity with building and using CI/CD pipelines.
- Familiarity with DevOps tools such as Docker, Git, Terraform.
