Lead Data Scientist

Placements24; United States; Remote; USD 73,000 - 109,000; Full time

Benefits offered by this job

Performance bonus

Health insurance

Paid time off

Stock options

Dev budget for conferences/training

Remote work stipend

Access to cutting-edge technology

Job summary

Placements24 seeks a Lead Data Scientist to spearhead data science initiatives for a fintech client in a remote-first setup. You will mentor a team, design and deploy production ML models, and partner with engineering and product teams to create data-driven products.

You will shape data strategy, drive innovation, and stay ahead of AI trends while collaborating across disciplines in a fully distributed environment.

Qualifications

• Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of experience in data science or machine learning, with at least 2 years in a leadership role.
• Proven experience in developing and deploying machine learning models in production (e.g., classification, regression, clustering, deep learning).
• Expertise in programming languages such as Python or R, and associated data science libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas).
• Strong understanding of big data technologies (e.g., Spark, Hadoop) and SQL.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and leadership abilities, with experience mentoring junior team members.
• Experience with cloud platforms (AWS, Azure, GCP) is a plus.
• Familiarity with MLOps practices and tools.

Responsibilities

• Lead and mentor a team of data scientists, guiding their technical development and project execution.
• Design, develop, and deploy machine learning models and algorithms to solve complex business problems.
• Identify new data sources and opportunities for leveraging data analytics to drive business value.
• Collaborate with engineering teams to integrate data science models into production systems.
• Develop and maintain data pipelines, ensuring data quality and integrity.
• Communicate complex analytical findings and recommendations to stakeholders in a clear and concise manner.
• Drive innovation in data science methodologies and tools.
• Stay current with the latest advancements in machine learning, AI, and data science.
• Contribute to the company's data strategy and roadmap.
• Evaluate and implement new technologies and platforms to enhance data science capabilities.

Skills

Leadership

Python

R

MLOps

Cloud platforms

Communication

Team mentoring

Education

Master's or PhD in Computer Science, Statistics, Mathematics, or related quantitative field

Tools

TensorFlow

PyTorch

Scikit-learn

Pandas

Spark

Hadoop

SQL

Job description

About the Role

Our client, an innovative fintech company, is looking for a talented Lead Data Scientist to spearhead their data science initiatives in Klerksdorp . This role is pivotal in leveraging advanced analytics, machine learning, and AI to drive product innovation, enhance customer experiences, and optimize business operations. As a remote-first organization, we encourage collaboration and contribution from wherever you work best. You will lead a team of data scientists, mentor junior members, and collaborate with cross-functional teams including engineering, product, and marketing. The ideal candidate has a proven track record of building and deploying sophisticated data-driven solutions in a production environment. You should possess a deep understanding of statistical modeling, machine learning algorithms, and big data technologies. This is a fantastic opportunity to shape the future of data science within a rapidly growing company, working on challenging problems with significant business impact. We value creativity, technical excellence, and a passion for turning data into actionable insights. Your leadership will be key to driving our data strategy forward in this fully remote capacity.

Key Responsibilities

• Lead and mentor a team of data scientists, guiding their technical development and project execution.


• Design, develop, and deploy machine learning models and algorithms to solve complex business problems.


• Identify new data sources and opportunities for leveraging data analytics to drive business value.


• Collaborate with engineering teams to integrate data science models into production systems.


• Develop and maintain data pipelines, ensuring data quality and integrity.


• Communicate complex analytical findings and recommendations to stakeholders in a clear and concise manner.


• Drive innovation in data science methodologies and tools.


• Stay current with the latest advancements in machine learning, AI, and data science.


• Contribute to the company's data strategy and roadmap.


• Evaluate and implement new technologies and platforms to enhance data science capabilities.

Requirements

• Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.


• 5+ years of experience in data science or machine learning, with at least 2 years in a leadership role.


• Proven experience in developing and deploying machine learning models in production (e.g., classification, regression, clustering, deep learning).


• Expertise in programming languages such as Python or R, and associated data science libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas).


• Strong understanding of big data technologies (e.g., Spark, Hadoop) and SQL.


• Excellent analytical, problem-solving, and critical thinking skills.


• Strong communication and leadership abilities, with experience mentoring junior team members.


• Experience with cloud platforms (AWS, Azure, GCP) is a plus.


• Familiarity with MLOps practices and tools.

Benefits

• Highly competitive salary and performance bonus.


• Comprehensive health insurance coverage.


• Generous paid time off and flexible working hours.


• Stock options or equity participation.


• Professional development budget for conferences and training.


• Fully remote work environment with home office stipend.


• Access to cutting-edge technology stack.


• Collaborative and innovative company culture.