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