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Open nowFirst seen 3 days ago

Senior Data Scientist

Boardroom Appointments3,354 open roles

Where
Johannesburg, South Africa
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Your applicationOpen nowSenior Data ScientistBoardroom Appointments · Johannesburg, South Africa
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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 3 days ago

The posting

Senior Data Scientist

Minimum Requirements:

  • Matric (Grade 12)
  • Advanced Diplomas/National 1st Degrees

Responsibilities:

  • Spearheaded best-in-class statistical models and algorithms, building upon previous experiences and learnings.
  • Conduct in-depth statistical analysis to extract valuable insights and patterns from complex datasets, contributing to data-driven decision making.
  • Offer actionable insights and advice to stakeholders, utilizing a solid foundation in AI/ML and contributing to the team's expertise.
  • Contribute to the creation of value from enterprise-wide data, assisting in the translation of data into meaningful business solutions.
  • Apply specific financial services domain knowledge to analyse datasets and develop statistical models and algorithms that cater to individual financial services use cases.
  • Design and implement ML models with experienced banking professionals that meet the unique requirements of financial institutions.
  • Implementation of cutting-edge AI and ML solutions, playing an active role in system operations and maintenance.
  • Experienced in deploying or contributed to deployment of at least one end to end data science solutions that has yielded significant value in the organisation at an enterprise level.
  • Contribute to the shaping of the organization's AI/ML strategy, aligning it with evolving business needs.
  • Assist in transforming data science prototypes into scalable machine learning solutions for deployment.
  • Collaborate with experienced team members to design dynamic ML models and systems, incorporating the capability for adaptability and retraining.
  • Participate in periodic evaluations of ML systems, ensuring they align with corporate and IT strategies.
  • Expert proficiency in programming tools (such as Python, R, etc) for data manipulation, statistical analysis, and machine learning tasks is essential.
  • Demonstrate a profound command over computer science fundamentals, encompassing expert-level knowledge of data structures, algorithms, computability and complexity, and computer architecture.
  • Demonstrate a strong understanding of applications and machine learning algorithms, aligned to best practices globally.
  • Spearheading and guiding the software engineering and design facets of projects, while providing mentorship and fostering collaboration among cross-functional teams.
  • Utilize machine learning algorithms and libraries effectively, following established best practices and guidelines.
  • Communicate technical concepts effectively to diverse audiences, adapting explanations for non-programming experts.
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