Senior Data Scientist - Financial Analytics

Placements24; Mtubatuba Local Municipality; Hybrid; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Competitive salary

Health insurance

Remote-friendly

Conference participation

Job summary

Placements24 is seeking a Senior Data Scientist in Richards Bay to lead ML projects for financial forecasting, risk assessment, and anomaly detection. You will design, deploy, and scale data-driven solutions across finance teams, guiding stakeholders from concept to deployment.

The role requires a PhD or Master’s in a quantitative field, 5+ years in data science with financial analytics, and strong Python/R expertise plus Spark/Hadoop and SQL. Remote-friendly with collaboration across teams.

Qualifications

• PhD or Master’s degree in a quantitative field such as Data Science or CS.
• 5+ years of experience as a Data Scientist with a focus on financial analytics.
• Proficiency in Python or R and key libraries (scikit-learn, TF, PyTorch).
• Experience with big data tech (Spark, Hadoop) and SQL.
• Strong statistical modelling, ML algorithms, and experimental design.

Responsibilities

• Design, develop, and deploy ML models for financial forecasting and risk assessment.
• Analyze large financial datasets to identify trends and actionable insights.
• Collaborate with business units to translate needs into data science solutions.
• Build and maintain data pipelines ensuring data quality and integrity for analysis.
• Communicate findings clearly to technical and non-technical audiences.

Skills

Python

R

scikit-learn

TensorFlow

PyTorch

Spark

Hadoop

SQL

Statistical modelling

Experiment design

Education

PhD or Master's in Data Science/CS/Statistics

Tools

Spark

Hadoop

SQL

Job description

Our client is seeking an accomplished Senior Data Scientist with a specialization in Financial Analytics to join their innovative team in Richards Bay . This role focuses on leveraging advanced data techniques to derive insights from complex financial datasets, driving strategic decisions and improving risk management, fraud detection, and customer behavior analysis. You will lead data science projects from conception to deployment, collaborating closely with business stakeholders to translate data into tangible business value within the banking sector. The ideal candidate is passionate about uncovering patterns in data and applying cutting-edge methodologies to solve challenging financial problems.

Key Responsibilities

• Design, develop, and deploy machine learning models for financial forecasting, risk assessment, and anomaly detection.
• Analyze large, complex datasets to identify key trends, patterns, and actionable insights relevant to financial operations .
• Collaborate with business units to understand their needs and translate them into data science solutions.
• Build and maintain data pipelines and ensure the quality and integrity of data used for analysis.
• Communicate complex findings and recommendations clearly to both technical and non-technical audiences.
• Stay abreast of the latest advancements in data science, machine learning, and financial technology .

Requirements

• Ph.D. or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of experience as a Data Scientist, with a significant focus on financial analytics .
• Proficiency in programming languages such as Python or R, and expertise in relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Strong experience with big data technologies (e.g., Spark, Hadoop) and SQL.
• Deep understanding of statistical modeling, machine learning algorithms, and experimental design.
• Excellent problem-solving skills and the ability to work independently in a remote setting.

Benefits

• Highly competitive salary and an excellent bonus structure.
• Comprehensive health, dental, and vision insurance plans.
• Significant opportunities for professional growth and attending leading conferences.
• Flexible remote working arrangements.
• Access to state-of-the-art computing resources and datasets.
• A stimulating and collaborative environment pushing the boundaries of data science in finance .