Data Science Engineer

Company Description

Eldridge Morgan is an analytics and technology firm partnering with large-scale enterprise clients across the US to build data systems that drive measurable business outcomes. We work at the intersection of applied machine learning, statistical modelling, and engineering — turning complex customer data into decisions that affect the P&L.

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

Looking to advance your Data Science career with relocation support? Explore Data Science Jobs with Relocation Packages that include comprehensive packages to help you move and settle in your new role.

• 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, PyTorch or equivalent
• Hands-on experience with churn, attrition, or customer lifecycle modelling

Discover our full range of relocation jobs with comprehensive support packages to help you relocate and settle in your new location.

• 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
• Location: Bhubaneswar, Odisha — relocation expected

If you have public work on GitHub, Kaggle, or research related to churn, time series, or probabilistic modelling — include it in your application.