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Machine Learning Engineer Position in Sandton - Discovery


Job description

Discovery Insure

Machine Learning Engineer

About Discovery

Discovery’s core purpose is to make people healthier and to enhance and protect their lives.

We seek out and invest in exceptional individuals who understand and support our core purpose, and whose own values align with those of Discovery.

Our fast-paced and dynamic environment enables smart, self-driven people to be their best.

As global thought leaders, Discovery is passionate about innovating in order to not only achieve financial success, but to ignite positive and meaningful change within our society .

About Discovery Insure

Discovery Insure is committed to creating a nation of great drivers through our innovative Shared-value Insurance model.

Discovery Insure is South Africa’s fastest growing short-term insurance company with comprehensive products that provide protection against current and emerging risks facing clients in the motor and home insurance sectors.

Vitality Drive, an internationally-recognised and award-winning programme, is a key differentiator in the market that incentivises and rewards clients for driving well.

The Vitality Drive programme has been scaled to local and international markets which now include Europe and the Middle East.

The company employs over 1 000 people who are committed to putting our customers and financial advisers first by providing unique and innovative solutions and cover.

Key Purpose

This ML Engineer is responsible for designing, building, managing, and continuously improving the operational processes that support the deployment and maintenance of actuarial, machine learning, and other decision-support models.

The role involves end-to-end project planning, cross-functional collaboration with actuarial, data science, analytics, and business teams, and delivering insights into process efficiency across business areas.

It also includes reporting on the design, progress, and performance of models and related business processes to drive operational excellence and informed decision-making.

Areas of responsibility may include but are not limited to

  • Design and create implementation and testing processes for models in both a traditional and ML framework to ensure business decisions can be actioned quickly and effectively.

  • Assist with the design and integration of traditional models and processes into cloud-based platforms like DataBricks to utilise additional functions and better performance.

  • Responsible for deploying rating and logic engines using proprietary software, ensuring accurate implementation and seamless integration into production environments.

  • Project planning and collaboration with actuarial, data science, underwriting, operational and system teams to ensure a smooth implementation process that reduces risks and achieves the required outcomes.

  • Frequent monitoring and reporting on the progress and performance of existing models and processes, as well as presenting the design for new processes to upper management.

  • Creation of automated processes and reports to reduce manual intervention and flag any areas of concern as they arise.

  • Assessment of the efficiency and effectiveness of business processes through data analytics to identify any areas for improvement or cost savings.

  • Implementation of pricing changes in existing models on a frequent basis, to ensure that changes in our pricing structure and strategies can be quickly actioned.

  • Creation of new tools and processes that can be used to reduce manual intervention and turnaround time of our client support teams.

Skills and Knowledge:

  • Modelling skills preferred (Basic)
  • Programming Skills: SQL, Python (Intermediate)
  • Microsoft Office (Excel, PowerPoint and Word) (Advanced)

Education and Experience

Education:

  • Matric (Essential)
  • Honours degree in Actuarial Science and/or Mathematical Statistics/ Computer Science or Data Science (Essential)
  • Min 3-5 completed CT subjects if Actuarial Degree (Advantageous)

Minimum Experience:

  • At least 1-3 years’ experience within a data driven industry
  • Experience with Databricks
  • Experience with Azure ML solutions
  • Experience with WTW Software (e.g., Radar Live) (advantageous)

EMPLOYMENT EQUITY

The Company’s approved Employment Equity Plan and Targets will be considered as part of the recruitment process.

As an Equal Opportunities employer, we actively encourage and welcome people with various disabilities to apply.

#J-18808-Ljbffr

Required Skill Profession

Engineering


  • Job Details

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Unlock Your Machine Learning Potential: Insight & Career Growth Guide


Real-time Machine Learning Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for Machine Learning in Sandton, South Africa, highlighting market share and opportunities for professionals in Machine Learning roles.

1018 Jobs in South Africa
1018
13 Jobs in Sandton
13
Download Machine Learning Jobs Trends in Sandton and South Africa

Are You Looking for Machine Learning Engineer Job?

Great news! is currently hiring and seeking a Machine Learning Engineer to join their team. Feel free to download the job details.

Wait no longer! Are you also interested in exploring similar jobs? Search now: .

The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Discovery adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying South Africa laws and regulations

What Is the Average Salary Range for Machine Learning Engineer Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Sandton. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

What Are the Key Qualifications for Machine Learning Engineer?

Key qualifications for Machine Learning Engineer typically include Engineering and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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To improve your chances of getting hired for Machine Learning Engineer, consider enhancing your skills. Check your CV/Résumé Score with our free Tool. We have an in-built Resume Scoring tool that gives you the matching score for each job based on your CV/Résumé once it is uploaded. This can help you align your CV/Résumé according to the job requirements and enhance your skills if needed.

Interview Tips for Machine Learning Engineer Job Success

Discovery interview tips for Machine Learning Engineer

Here are some tips to help you prepare for and ace your Machine Learning Engineer job interview:

Before the Interview:

Research: Learn about the Discovery's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

Be Positive: Focus on your strengths and accomplishments.

Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Machine Learning Engineer interview at Discovery, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Discovery's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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