Junior Data Analyst (Data Scientist)

Company Description • This opportunity is advertised on behalf of a partner company. All applications, interviews, and subsequent hiring steps will be managed directly by the partner organization. • Our partner is seeking a Junior Data Analyst / Data Scientist to join their remote team and contribute to data-driven projects across Financial Services, Retail, E-commerce, Logistics, Business Intelligence, Artificial Intelligence (AI), and Machine Learning (ML). • This role is well suited to an early-career data professional who is curious about how data can be used to solve business problems, uncover trends, and support better decision-making. • The successful candidate will have the opportunity to work on a variety of analytics and data science projects, ranging from business reporting and data visualization to predictive modeling and machine learning. Key Responsibilities • Collect, clean, transform, and analyze data from different internal and external sources • Use Python, SQL, and statistical techniques to investigate business and operational questions • Conduct Exploratory Data Analysis (EDA) to uncover trends, relationships, anomalies, and opportunities • Build and maintain reports, dashboards, KPIs, and Business Intelligence (BI) solutions • Perform descriptive and statistical analyses to support business and strategic decisions • Assist in developing and evaluating Machine Learning (ML) and predictive models • Contribute to customer, product, commercial, marketing, and operational analytics projects • Analyze areas such as customer behavior, transactions, sales performance, product usage, and operational efficiency • Support forecasting, customer segmentation, classification, and other predictive analytics initiatives • Assist with A/B testing, experimentation, and hypothesis-driven analysis • Develop clear and meaningful data visualizations to communicate analytical findings • Present insights and recommendations to both technical and non-technical stakeholders • Contribute to AI, automation, and other data-driven initiatives • Help identify opportunities to improve data quality, reporting processes, and analytical workflows • Work collaboratively with teams across Product, Engineering, Finance, Marketing, Operations, and Business • Translate business requirements and questions into structured analytical approaches Requirements • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, Business Analytics, Information Systems, or another quantitative discipline • Solid foundational knowledge of Python and SQL • Good understanding of statistics, probability, and fundamental data analysis concepts • Hands-on experience working with datasets and conducting Exploratory Data Analysis (EDA) • Familiarity with Python data and Machine Learning libraries such as pandas, NumPy, and scikit-learn • Experience with or understanding of dashboarding and reporting tools such as Power BI, Tableau, Looker, or similar platforms • Strong analytical thinking and problem-solving abilities • Ability to interpret data and communicate insights in a clear and structured manner • Strong written and spoken English • Comfortable working both independently and as part of a distributed, remote team Preferred Qualifications • Internship, academic, bootcamp, freelance, or personal project experience in Data Analytics, Data Science, Business Intelligence, or Machine Learning • Exposure to data-driven industries such as Financial Services, FinTech, Retail, E-commerce, Logistics, or Technology • Familiarity with Git and GitHub • Experience working with Jupyter Notebook • Basic exposure to cloud environments such as AWS, Microsoft Azure, or Google Cloud Platform (GCP) • Familiarity with modern data warehouses and platforms including BigQuery, Snowflake, Redshift, or Databricks • Experience using Excel or BI and visualization tools such as Power BI, Tableau, or Looker • Exposure to predictive modeling, Machine Learning, or statistical modeling techniques • Familiarity with Generative AI, Large Language Models (LLMs), or AI-based applications • Portfolio demonstrating practical data work, such as GitHub repositories, Kaggle notebooks, university assignments, bootcamp projects, or personal Data Analytics / Data Science projects Show more Show less