Senior Analyst - Data Science

Job description

About LatentView Analytics Founded in 2006, LatentView Analytics began with a shared passion for the world of data. Today, over 20 years on, we've grown into a close-knit community of people united by that same drive — solving real business challenges with data and AI. We work with industry leaders worldwide, specializing in end-to-end analytics that goes beyond the buzzwords to deliver genuine business impact. Our focus has stayed consistent since day one: helping clients derive meaningful insights and drive growth through a thoughtful, sustainable approach to data analytics and AI. Role Overview We are hiring Data Scientists to design, build, and operationalize statistical and machine learning solutions across our client engagements. You will work with large-scale and often distributed datasets to uncover patterns, build predictive models, and translate findings into decisions that matter to the business. The specific focus of your role — from applied ML and marketing analytics to platform engineering for GenAI — will be matched to your experience and specialization. Key Responsibilities • Model development: Design, build, and evaluate statistical and machine learning models against real business problems, from exploratory analysis through to production-quality solutions • Data engineering for analysis: Acquire, clean, and process data from large-scale or distributed sources, including feature engineering to strengthen model performance • Deployment & monitoring: Operationalize models into production pipelines, and monitor performance over time to catch drift, decay, or data-quality issues • Stakeholder collaboration: Work closely with business, product, engineering, risk, or compliance teams — as relevant to the project — to shape and deliver analytical solutions • Communication: Present findings, models, and recommendations clearly to both technical and non-technical audiences • Governance & reliability: Follow responsible AI, data governance, and security practices appropriate to the engagement Skills & Experience • 4–10 years of relevant experience in Data Science, Machine Learning, or a closely related analytics discipline • Strong programming skills in Python (or R) for data manipulation, model development, and evaluation • Proficiency in SQL for querying and processing data, including at scale (e.g. Spark SQL, Hive) •