Senior Data Scientist

2 weeks ago

Johannesburg, South Africa eSoft Development and Technologies Full time

**To be considered for this position you should have**:

- A Bachelor’s degree in Economics, Finance, Statistics, Data Science or Computer Science
- At least 3+ years of experience in R programming (rare exceptions for highly skilled developers) and developing solutions in
- Evidence of successfully completed projects (provide link to GitHub repos if possible; alternatively, provide a detailed description of relevant projects).
- Proficient with R programming
- Understanding of AI/ML algorithms and statistical computing
- Working knowledge of descriptive analytics, predictive analysis, and statistics
- Expertise in one or more scripting languages, such as Python, Perl, etc.
- Proficient with database technologies such as SQL
- experience with Data sources and Databases interfaces.
- Experience with RUnit for testing and REST APIs
- Knowledge of business analysis, system design, and business process re-engineering
- Fluent in English to communicate effectively
- Strong communication and interpersonal skills working with diverse teams. The following will be an added advantage
- Comfortable with Agile project delivery methodologies
- Excellent analytical and interpersonal skills
- Knowledge of R-Studio and Python

**Competencies**:

- High proficiency in developing end-to-end automated solutions using R statistical computing software
- Excellent knowledge of R Markdown or Quarto files (including customised LaTeX output)
- Strong knowledge of the following R packages would be advantageous: dplyr, tidyr, ggplot2, purrr, stringr, readxl, knitr, glue, gt, kableExtra, testthat
- Knowledge of working with the renv package for package versioning would be advantageous
- Knowledge of RStudio Workbench, RStudio Connect and RStudio Package Manager would be beneficial
- High proficiency in using Git version control in conjunction with GitHub

**Additional requirements include**:

- Be task-orientated, with time management skills to operate in a deadline-driven
- Environment that often requires working under pressure
- Be a motivated self-starter with the ability to develop innovative solutions to complex problems
- Be able to work independently as well as within a team/project environment.
- Good communication and interpersonal skills Analytical skills
- Building trust
- Service orientation
- Decision making
- Verbal and written communication
- Time and work management
- Problem solving and analysis
- Contribute to team success
- Solid knowledge of the Software Development life cycle

**Qualifications/ Certification**:

- A Bachelor’s degree in Economics, Finance, Statistics, Data Science or Computer Science
- At least five years’ professional experience developing solutions in R and Evidence of successfully completed projects (provide link to GitHub repos if possible; alternatively, provide a detailed description of relevant projects).

**The following will be an added advantage**
- Master’s degree in Engineering, Computer Science, Mathematics, IT (or equivalent experience)

**Key deliverables**
- R Markdown files for each report that are linked to the Shiny front-end: Memorandum - Commercial Banks claims
- Memorandum - Claims to NT o LGS Quarterly Report to NT
- LGS Operation Report
- Memorandum - Amortisation schedule reconciliation report final
- Memorandum - Management accounts
- LGSGC Trend Analysis Report
- An R Markdown file that performs validation checking and testing of the final produced values to ensure accuracy and highlight any potential error outcomes
- Detailed documentation of the developed solutions, including breakthroughs, using R Markdown Producing the following artefacts
- Timeline documents
- Technical solution document
- Unit testing document
- Maintenance Manual
- Deployment documents
- Release Notes
- Change Request documentation
- Working ICT solution

**Job Type**: Temporary
Contract length: 12 months

**Education**:

- Bachelors (preferred)

**Experience**:

- R programming: 3 years (preferred)
- developing solutions in R: 5 years (preferred)
- Data Scientist: 6 years (preferred)

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