Junior Data Analyst / Data Scientist

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 Analyst / Data Scientist to join their remote team and support data-driven decision-making across Financial Services, Retail, E-commerce, Logistics, Business Intelligence, Artificial Intelligence (AI), and Machine Learning (ML). • The role is ideal for an early-career data professional who enjoys working with data, identifying meaningful patterns, building analytical solutions, and turning complex datasets into actionable business insights. • The successful candidate will work across analytics and data science initiatives, supporting reporting, business intelligence, predictive analytics, experimentation, and machine learning projects. Key responsibilities include: • Analyze structured and unstructured datasets using Python, SQL, and statistical methods • Perform Exploratory Data Analysis (EDA) to identify trends, patterns, anomalies, and business opportunities • Develop recurring reports, dashboards, KPIs, and Business Intelligence (BI) solutions • Extract, clean, transform, and validate data from multiple sources • Conduct descriptive and statistical analysis to support business decisions • Develop basic predictive and Machine Learning (ML) models under the guidance of senior team members • Support customer, product, sales, marketing, and operational analytics initiatives • Analyze customer behavior, business performance, transactions, and operational metrics • Assist with forecasting, segmentation, classification, and predictive analytics projects • Design and analyze A/B tests, experiments, and hypothesis tests when required • Create data visualizations and communicate insights to technical and non-technical stakeholders • Support Artificial Intelligence (AI), automation, and data-driven business initiatives • Identify opportunities to improve reporting, analytics workflows, and data quality • Collaborate with Product, Engineering, Finance, Marketing, Operations, and Business teams • Translate business questions into analytical problems and data-driven recommendations Requirements • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, Business Analytics, Information Systems, or a related quantitative field • Strong foundational knowledge of Python and SQL • Understanding of statistics, probability, and data analysis concepts • Experience working with datasets and performing Exploratory Data Analysis (EDA) • Familiarity with pandas, NumPy, scikit-learn, or similar Python libraries • Experience creating dashboards or reports using Tableau, Power BI, Looker, Metabase, or similar BI tools • Strong analytical and problem-solving skills • Ability to communicate analytical findings clearly to technical and non-technical stakeholders • 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 Analytics, Data Science, Business Intelligence, or Machine Learning • Exposure to Financial Services, FinTech, Retail, E-commerce, Logistics, or other data-intensive industries • Familiarity with Git and GitHub • Experience using 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 Excel, Tableau, Power BI, Looker, or similar analytics tools • Exposure to Machine Learning, Predictive Analytics, or Statistical Modeling • Exposure to Generative AI, Large Language Models (LLMs), or AI-powered applications • GitHub portfolio, Kaggle projects, university projects, bootcamp projects, or personal Data Analytics / Data Science projects Show more Show less

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, Business Analytics, Information Systems, or a related quantitative field. Strong foundational knowledge of Python and SQL. Understanding of statistics, probability, and data analysis concepts. Experience working with datasets and performing Exploratory Data Analysis (EDA). Familiarity with pandas, NumPy, scikit-learn, or similar Python libraries. Experience creating dashboards or reports using Tableau, Power BI, Looker, Metabase, or similar BI tools. Strong analytical and problem-solving skills. Ability to communicate analytical findings clearly to technical and non-technical stakeholders. Strong written and verbal English communication skills. Ability to work independently and collaboratively in a remote environment.

Analyze structured and unstructured datasets using Python, SQL, and statistical methods; Perform Exploratory Data Analysis (EDA) to identify trends, patterns, anomalies, and business opportunities; Develop recurring reports, dashboards, KPIs, and BI solutions; Extract, clean, transform, and validate data from multiple sources; Conduct descriptive and statistical analysis to support business decisions; Develop basic predictive and Machine Learning (ML) models under the guidance of senior team members; Support customer, product, sales, marketing, and operational analytics initiatives; Analyze customer behavior, business performance, transactions, and operational metrics; Assist with forecasting, segmentation, classification, and predictive analytics projects; Design and analyze A/B tests, experiments, and hypothesis tests when required; Create data visualizations and communicate insights to technical and non-technical stakeholders; Support AI, automation, and data-driven business initiatives; Identify opportunities to improve reporting, analytics workflows, and data quality; Collaborate with Product, Engineering, Finance, Marketing, Operations, and Business teams; Translate business questions into analytical problems and data-driven recommendations.