Junior Data Scientist

About the job
This position is being offered on behalf of a partner organization. The partner company will be responsible for managing the application, interview, selection, and hiring process.
Our partner is looking for a Junior Data Analyst / Data Scientist to support its remote team across a range of data-focused initiatives within Financial Services, Retail, E-commerce, Logistics, Business Intelligence, Artificial Intelligence (AI), and Machine Learning (ML).
The position is designed for an early-career professional who enjoys working with data, solving practical problems, identifying meaningful patterns, and turning analysis into actionable business insights.
The selected candidate will gain exposure to diverse data projects, including business analytics, reporting, visualization, statistical analysis, predictive analytics, and Machine Learning applications.
Key Responsibilities
Gather, organize, validate, and prepare data from multiple business and external sources
Apply Python, SQL, statistics, and analytical methods to answer business-related questions
Explore datasets to identify patterns, trends, inconsistencies, correlations, and potential business opportunities
Create and support dashboards, performance reports, KPIs, and Business Intelligence (BI) reporting solutions
Conduct statistical and descriptive analyses to help teams make informed operational and strategic decisions
Support the development, testing, and performance evaluation of predictive and Machine Learning models
Work on analytics initiatives related to customers, products, sales, marketing, finance, and business operations
Investigate customer activity, purchasing patterns, revenue performance, product engagement, and operational metrics
Assist with forecasting, segmentation, classification, recommendation, and other predictive analytics use cases
Support experimentation, A/B testing, and data-driven hypothesis validation
Build effective visualizations that make complex findings easier to understand
Communicate analytical results, key findings, and recommendations to technical and business stakeholders
Participate in AI, automation, and other initiatives designed to improve data-driven decision-making
Identify opportunities to enhance data accuracy, reporting efficiency, and analytical processes
Collaborate with cross-functional teams including Product, Engineering, Finance, Marketing, Operations, and Business teams
Convert business needs into clearly defined analytical questions, methodologies, and deliverables
Requirements
Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, Business Analytics, Information Systems, or a related quantitative field
Working knowledge of Python and SQL
Fundamental understanding of statistics, probability, and data analysis methodologies
Practical experience analyzing datasets and performing Exploratory Data Analysis (EDA)
Familiarity with Python libraries used for data analysis and Machine Learning, including pandas, NumPy, and scikit-learn
Understanding of business reporting and visualization platforms such as Power BI, Tableau, Looker, or comparable tools
Strong quantitative reasoning, analytical thinking, and problem-solving skills
Ability to transform analytical results into clear and understandable business insights
Strong verbal and written English communication skills
Ability to manage tasks independently while collaborating effectively within a remote and distributed environment
Preferred Qualifications
Previous experience through internships, university projects, bootcamps, freelance assignments, or personal projects involving Data Analytics, Data Science, Business Intelligence, or Machine Learning
Experience or familiarity with industries such as Financial Services, FinTech, Retail, E-commerce, Logistics, or Technology
Working knowledge of Git and GitHub
Experience using Jupyter Notebook for analysis and experimentation
Basic familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP)
Exposure to modern data platforms and warehouses such as BigQuery, Snowflake, Amazon Redshift, or Databricks
Experience with Excel and/or business intelligence and visualization platforms including Power BI, Tableau, or Looker
Familiarity with predictive analytics, Machine Learning algorithms, or statistical modeling
Awareness of Generative AI, Large Language Models (LLMs), and AI-powered tools or applications
A portfolio showcasing practical analytical work, including GitHub repositories, Kaggle projects, academic coursework, bootcamp assignments, or independent Data Analytics / Data Science projects

Work arrangement
Yes