Company Description
- This position is listed on behalf of a partner company, which manages all applications and next steps.
- Our partner is looking for a Junior Data Scientist to join their remote team and support data-driven decision-making across Financial Services, FinTech, Artificial Intelligence (AI), Machine Learning (ML), Risk Analytics, Customer Analytics, and Business Intelligence.
- The role is designed for an early-career data professional who is passionate about using data to solve real-world financial and business problems. The Junior Data Scientist will work with structured and unstructured datasets, develop analytical and machine learning solutions, identify patterns and trends, and collaborate with cross-functional teams to turn data into actionable insights.
Accountabilities
The Junior Data Scientist will work closely with Data Science, Engineering, Product, Risk, Finance, and Business teams to develop data-driven solutions and support strategic initiatives.
Key responsibilities include:
- Analyze structured and unstructured financial and business data using Python, SQL, and statistical methods
- Perform Exploratory Data Analysis (EDA) to identify trends, patterns, anomalies, and business opportunities
- Develop and evaluate Machine Learning (ML) models for prediction, classification, segmentation, and forecasting
- Support financial risk analytics, fraud detection, customer analytics, and operational analytics initiatives
- Build data visualizations, dashboards, reports, and KPIs to communicate analytical findings
- Perform statistical analysis, hypothesis testing, and experimentation
- Assist with predictive modeling and forecasting projects
- Identify patterns in customer behavior, transactions, financial performance, and operational data
- Support Artificial Intelligence (AI), automation, and data-driven product initiatives
- Clean, transform, validate, and prepare datasets for analysis and modeling
- Collaborate with Data Scientists, Data Engineers, Software Engineers, Product Managers, Risk Analysts, and business stakeholders
- Communicate analytical findings and recommendations to technical and non-technical audiences
- Contribute to improving data quality, analytical workflows, documentation, and reporting processes
Requirements
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Economics, Engineering, Business Analytics, Information Systems, or a related quantitative field
- 0–2 years of experience in Data Science, Data Analytics, Business Analytics, Machine Learning, or a related field
- Strong foundational knowledge of Python and SQL
- Understanding of Machine Learning concepts and common modeling techniques
- Knowledge of statistics, probability, hypothesis testing, and experimental design
- Experience performing Exploratory Data Analysis (EDA)
- Familiarity with data visualization tools such as Tableau, Power BI, Looker, or similar platforms
- Familiarity with pandas, NumPy, scikit-learn, or similar Python data science libraries
- Strong analytical and problem-solving skills
- Ability to work with large datasets and identify meaningful patterns
- Strong written and verbal English communication skills
- Ability to work independently and collaboratively in a remote environment
Preferred Qualifications
- Internship, academic, bootcamp, or project experience in Data Science, Machine Learning, Analytics, or FinTech
- Exposure to financial datasets, transaction data, credit risk, fraud detection, or customer analytics
- Familiarity with Git and GitHub
- Experience with Jupyter Notebook
- Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP)
- Exposure to BigQuery, Snowflake, Redshift, Databricks, or other modern data platforms
- Experience with Tableau, Power BI, Looker, or similar BI tools
- Exposure to Generative AI, Large Language Models (LLMs), or AI-powered applications