Junior Data Scientist

Junior Data Scientist – Business Operations & Analytics Summary We are seeking a highly analytical and strategic Junior Data Scientist to drive data-led decision making across a large-scale customer and business operations environment. This role will focus on leveraging advanced analytics, reporting, and data modelling to uncover actionable insights, improve operational performance, and influence business strategy. The ideal candidate thrives in ambiguous environments, can independently manage complex cross-functional initiatives, and is passionate about transforming data into meaningful business outcomes. Responsibilities Develop and execute data science and analytics strategies that support business objectives and operational excellence. Design, build, and maintain advanced analytical models, prototypes, and frameworks to identify trends, opportunities, and performance improvements. Extract, process, and analyze large, complex datasets using SQL, Python, R, and Big Data technologies. Create and maintain scalable dashboards, reporting systems, KPIs, and operational metrics to support business performance monitoring. Translate complex analytical findings into clear, actionable recommendations for technical and non-technical stakeholders. Partner closely with cross-functional teams including Operations, Product, Engineering, and Business Leadership to solve complex business challenges. Drive data governance, reporting best practices, and continuous improvements in analytics methodologies. Mentor and support analysts and data professionals, fostering a culture of collaboration, innovation, and analytical excellence. Identify opportunities to automate reporting, streamline workflows, and improve operational efficiency through data-driven solutions. Present insights and strategic recommendations to senior leadership to influence decision-making and business direction. Requirements Essential Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative discipline. 2 - 3 years of experience in data analytics, data science, business intelligence, operations analytics, or a similar function. Advanced SQL skills, including the ability to build, optimize, and maintain complex queries against large datasets. Experience working with Big Data technologies and analytical tools such as Tableau, Hive, Presto, Python, and/or R. Strong understanding of operational metrics, KPIs, reporting frameworks, and performance measurement methodologies. Proven ability to perform exploratory analysis and derive actionable insights from complex datasets. Experience designing dashboards, reports, and visualizations that support business decision-making. Excellent communication and stakeholder management skills, with the ability to explain technical concepts to diverse audiences. Strong problem-solving mindset with the ability to work independently in fast-paced and ambiguous environments. Preferred Experience supporting Customer Operations, Customer Support, Scaled Operations, Shared Services, or Business Operations functions. Experience working with large-scale datasets in high-growth technology, digital, e-commerce, or platform-based organizations. Knowledge of data pipeline architecture, ETL processes, and data warehousing concepts. Exposure to machine learning, predictive analytics, forecasting, or statistical modelling techniques. Demonstrated track record of driving measurable business impact through data-driven initiatives. Experience mentoring analysts or leading cross-functional analytics projects. This is an initial 12-months contract role