Data Science Engineer

Role

Description We are looking for a Data Science Engineer to work on customer churn forecasting, attrition modelling, and state space systems for a major US telecom engagement. This role sits at the boundary of data science and engineering you will own models from problem framing through to production. The ideal candidate has strong statistical foundations, writes clean Python, and has worked on time - dependent or behavioural modelling problems before. What does day - to - day look like - Build and maintain churn and attrition models using survival analysis, classification, and probabilistic approaches - Implement and work with state space models Linear Gaussian SSMs, HMMs, Kalman filters for tracking latent customer behaviour over time - Engineer features from raw telecom data including usage patterns, billing signals, and interaction histories - Design offline evaluation frameworks with correct temporal splits, calibration checks, and business - aligned metrics - Write production - ready Python code readable, documented, version - controlled, and reviewable - Deploy models via APIs and monitor for data drift and performance degradation - Collaborate with engineers and business stakeholders to translate churn signals into actionable interventions Requirements - 2 4 years of experience as a Data Scientist, ML Engineer, or Data Science Engineer - Strong proficiency in Python pandas, scikit - learn, statsmodels, Py

Torch or equivalent - Hands - on experience with churn, attrition, or customer lifecycle modelling - Working knowledge of state space models or time series methods you can explain what you implemented, not just that you used a library - Solid grasp of ML fundamentals loss functions, regularisation, model evaluation, calibration - Proficiency in SQL for working with large structured datasets - Experience with experiment tracking tools MLflow, DVC, or similar - Ability to read, navigate, and modify real - world codebases Who You Are Beyond the technical, we care about how you think and communicate. We work closely with US - based stakeholders and expect everyone on the team to hold their own in those conversations clearly, confidently, and without ambiguity. You do not need to have grown up speaking English, but you need to communicate in it like a professional who takes language seriously. We are building a team that does not just execute we want people who have opinions, push back when something does not make sense, and contribute to how the team thinks about problems. If you have written about data science, spoken at a meetup, mentored peers, or contributed to open source that tells us something meaningful about you. We value intellectual honesty over credentials, ownership over instructions, and clarity over cleverness. Offer Details - Compensation: Competitive, in line with industry standards for the experience band expect ballpark 6 9 LPA depending on demonstrated technical depth - Engagement Type: Full - time, on - site -

Hub, Kaggle, or research related to churn, time series, or probabilistic modelling include it in your application.