Lead Data Scientist - Fintech

Placements24; Cape Town; Hybrid; ZAR 900,000 - 1,400,000; Full time

Benefits offered by this job

Remote work

Stock options

Annual bonus

Health insurance

Professional development budget

Job summary

Placements24 seeks a Lead Data Scientist to drive advanced analytics in a fully remote fintech environment. You will design, implement, and deploy cutting-edge ML models for fraud detection, risk assessment, and customer segmentation while mentoring a team of data scientists.

You will collaborate with product and engineering to productionize solutions, build robust data pipelines, and promote best practices in experimentation and data science culture across the organization.

Qualifications

• Advanced degree (Master's or PhD) in Data Science, CS, Statistics, or related field.
• 8+ years of data science experience with leadership.
• Expertise in ML algorithms, statistical modeling, and predictive analytics.
• Proficiency in Python or R with libraries (TensorFlow, PyTorch, scikit-learn).
• Experience with Spark/Hadoop and cloud platforms (AWS/Azure/GCP).
• Strong communication and leadership skills to explain complex concepts.

Responsibilities

• Lead design, development, and deployment of ML models (fraud, risk, segmentation).
• Mentor and guide a team of data scientists, fostering growth.
• Collaborate with product management and engineering to productionize solutions.
• Conduct exploratory data analysis to uncover opportunities from large datasets.
• Develop and maintain data pipelines and experiment frameworks.
• Stay updated on advances in data science and apply to business problems.

Skills

Team leadership

Data science

Machine learning

Python

R

Cloud platforms

Big data

Communication

Education

Master's degree

PhD

Tools

TensorFlow

PyTorch

scikit-learn

Spark

Hadoop

AWS

Azure

GCP

Job description

About the Role

Our client is seeking an experienced and visionary Lead Data Scientist to drive their advanced analytics initiatives within the fintech sector, based remotely. This role is critical for developing and implementing cutting-edge machine learning models and data-driven strategies that will shape the future of our financial products and services. You will lead a team of talented data scientists, mentor junior members, and collaborate with engineering and product teams to deploy sophisticated solutions. This is an exceptional opportunity to work in a fully remote, agile environment, tackling complex challenges and influencing product development with your deep analytical expertise. You will champion data science best practices and foster a culture of innovation and continuous learning.

Key Responsibilities

• Lead the design, development, and deployment of machine learning models for applications such as fraud detection, risk assessment, and customer segmentation.
• Mentor and guide a team of data scientists, fostering their technical and professional growth.
• Collaborate with product management and engineering teams to integrate data science solutions into production systems.
• Conduct exploratory data analysis to identify new opportunities and insights from large, complex datasets.
• Develop and maintain robust data pipelines and experiment frameworks.
• Stay abreast of the latest advancements in data science, machine learning, and AI, and apply them to business problems.

Requirements

• Advanced degree (Master's or PhD) in Data Science, Computer Science, Statistics, or a related quantitative field.
• 8+ years of experience in data science, with a proven track record of leading projects and teams.
• Expertise in machine learning algorithms , statistical modeling, and predictive analytics.
• Proficiency in programming languages like Python or R, and experience with relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Strong communication and leadership skills, with the ability to explain complex technical concepts to non-technical audiences.

Benefits

• Highly competitive salary and annual bonus structure.
• Full remote work arrangement with flexible hours.
• Generous stock options and long-term incentive plans.
• Comprehensive health, dental, and vision insurance coverage.
• Professional development budget for conferences and training.