Junior Data Scientist

About the jobThis 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 ResponsibilitiesGather, organize, validate, and prepare data from multiple business and external sourcesApply Python, SQL, statistics, and analytical methods to answer business-related questionsExplore datasets to identify patterns, trends, inconsistencies, correlations, and potential business opportunitiesCreate and support dashboards, performance reports, KPIs, and Business Intelligence (BI) reporting solutionsConduct statistical and descriptive analyses to help teams make informed operational and strategic decisionsSupport the development, testing, and performance evaluation of predictive and Machine Learning modelsWork on analytics initiatives related to customers, products, sales, marketing, finance, and business operationsInvestigate customer activity, purchasing patterns, revenue performance, product engagement, and operational metricsAssist with forecasting, segmentation, classification, recommendation, and other predictive analytics use casesSupport experimentation, A/B testing, and data-driven hypothesis validationBuild effective visualizations that make complex findings easier to understandCommunicate analytical results, key findings, and recommendations to technical and business stakeholdersParticipate in AI, automation, and other initiatives designed to improve data-driven decision-makingIdentify opportunities to enhance data accuracy, reporting efficiency, and analytical processesCollaborate with cross-functional teams including Product, Engineering, Finance, Marketing, Operations, and Business teamsConvert business needs into clearly defined analytical questions, methodologies, and deliverablesRequirementsBachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, Business Analytics, Information Systems, or a related quantitative fieldWorking knowledge of Python and SQLFundamental understanding of statistics, probability, and data analysis methodologiesPractical 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-learnUnderstanding of business reporting and visualization platforms such as Power BI, Tableau, Looker, or comparable toolsStrong quantitative reasoning, analytical thinking, and problem-solving skillsAbility to transform analytical results into clear and understandable business insightsStrong verbal and written English communication skillsAbility to manage tasks independently while collaborating effectively within a remote and distributed environmentPreferred QualificationsPrevious experience through internships, university projects, bootcamps, freelance assignments, or personal projects involving Data Analytics, Data Science, Business Intelligence, or Machine LearningExperience or familiarity with industries such as Financial Services, FinTech, Retail, E-commerce, Logistics, or TechnologyWorking knowledge of Git and GitHubExperience using Jupyter Notebook for analysis and experimentationBasic 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 DatabricksExperience with Excel and/or business intelligence and visualization platforms including Power BI, Tableau, or LookerFamiliarity with predictive analytics, Machine Learning algorithms, or statistical modelingAwareness of Generative AI, Large Language Models (LLMs), and AI-powered tools or applicationsA portfolio showcasing practical analytical work, including GitHub repositories, Kaggle projects, academic coursework, bootcamp assignments, or independent Data Analytics / Data Science projects