Data Scientist (ML & Statistics)

Loyalty Juggernaut, Inc; Hyderabad; Vor Ort; INR 1.200.000 - 2.400.000; Vollzeit

Zusammenfassung

Loyalty Juggernaut, Inc. is seeking a Data Scientist to turn statistical ideas into real-world predictive models. You will work on churn, propensity, next-best-offer, and lifetime value models using large member datasets.

The role blends heavy modeling with business framing and client interaction to drive decisions. You will partner with Product, Data Engineering, and Customer Success to deploy models in production and communicate their impact to stakeholders.

Qualifikationen

• Bachelor's or Master's in a quantitative field; MBA adds value.
• 1–4 years building and deploying ML models in production, SaaS or loyalty/CRM preferred.
• Strong Python and SQL with experience in ML libraries (scikit-learn, XGBoost/LightGBM).

Aufgaben

• Design, train and validate churn, propensity, LTV, and anomaly models.
• Develop and productionize predictive and causal models on large member data.
• Explain model impact to client stakeholders and translate results into decisions.
• Collaborate with Product, Data Engineering, Engineering and Customer Success.

Kenntnisse

Python

SQL

Statistical Modeling

Machine Learning

Time-series Analysis

A/B Testing

Data Visualization

Communication

Ausbildung

Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Engineering, Data Science or related quantitative field

MBA or analytics postgrad degree (added advantage)

Tools

Snowflake

BigQuery

Redshift

Databricks

Spark

TensorFlow

PyTorch

Tableau

Power BI

Looker

Jobbeschreibung

CrunchNumbers.BuildModels.ShapeStrategy.CreateImpact!

About LJI

Loyalty Juggernaut (LJI) is a leading B2B SaaS company redefining how enterprises drivecustomer engagement and loyalty. Our flagship platform, GRAVTY®, enables globalbrands to turn loyalty programs into measurable, revenue-generating growth engines.
Built as an AI-first, next-generation solution, GRAVTY® helps organizations deliverpersonalized, real-time experiences at scale, increasing customer lifetime value anddeepening brand relationships. Headquartered in Palo Alto, California, LJI partners withenterprises across 16 major industries, including airlines, retail, hospitality, financialservices and telecommunications.

OurGlobalImpact:

• 400+Millionmembersconnectedthroughourplatform.
• 100+GlobalBrandstrustustodriveloyaltyandbranddevotion.
• 3-TimeWinnerof“BestTechnologyInnovationinLoyalty”.
• GlobalrecognitionsforExcellenceinLoyaltyManagementundernumerouscategories.
• Recognizedasa‘Strongperformer’inTheForresterWave™LoyaltyPlatforms,Q42025.

Exploremoreaboutusat www.lji.io.

Role Overview

We are seeking a Data Scientist who can turn statistical ideas into models that loyaltyclients rely on every day. You will build predictive and causal models on member-leveldata from programs with millions of members, run them reliably in production, and explaintheir impact to client stakeholders.

The role is roughly70% technical(modeling, statistics, engineering of ML systems) and30% business(framing problems, working with clients, translating results into decisions).You will work closely with Product, Data Engineering, Engineering and Customer Success.

What you will OWN

Design, train and validate models for churn,propensity, next-best-offer, lifetime value, tier migration and anomaly or fraud detection.Choose methods on evidence: regression and GLMs, survival analysis, gradient boosting, probabilistic and Bayesian models, time-series forecasting, and deep learning where itearns its complexity.

Experimentation & Causal Inference (technical)

Design A/B tests and holdouts forcampaigns, offers and program changes, including power analysis and sample sizing.Apply uplift modeling and causal methods (diff-in-diff, propensity matching) to measurethe true incremental impact of loyalty initiatives when randomization is not possible.

Feature Engineering & Data Pipelines (technical)

Build and maintain reusable featuresets from large transactional and behavioral datasets. Work with Data Engineering ondata quality, lineage and scalable processing in the data warehouse and cloud platform.

Client Engagement & Insight Delivery (business)

Partner with client stakeholders toframe business questions as modeling problems, define success metrics, and presentresults and recommendations in executive reviews. Translate model outputs into clearactions for marketing, product and finance teams, and document models, assumptionsand limitations.

To be successful in this role, you should have:

• Bachelor's or Master's degree in Statistics, Mathematics, Computer Science,Engineering, Data Science or a related quantitative field. An MBA or a postgraduatedegree in Analytics is an added advantage.
• 1–4 years of experience building and deploying ML or statistical models in production,ideally in a SaaS, consumer or loyalty/CRM setting.
• Strong Python (pandas, NumPy, scikit-learn, XGBoost/LightGBM, statsmodels; PyTorchor TensorFlow is a plus) and strong SQL.
• Solid statistical foundations: hypothesis testing, regression, probability, Bayesianmethods, time-series, survival analysis and experimental design.
• Experience with cloud data platforms such as Snowflake, BigQuery, Redshift,Databricks or Vertica, and with large-scale data processing (Spark is a plus).
• Working knowledge of a BI tool (Tableau, Power BI, Looker or similar) to share modeloutputs.
• Experience with causal inference or uplift modeling is preferred.
• Exposure to enterprise SaaS products or customer loyalty programs is preferred.
• Strong communication skills: able to explain model logic, trade-offs and uncertainty tonon-technical stakeholders.
• Understanding of Agile methodologies and comfort working in a fast-pacedenvironment.

Key Competencies

• Statistical Modeling & Machine Learning
• Experimentation & Causal Thinking
• Production-Grade Engineering & MLOps
• Problem Solving & Root Cause Analysis
• Business Problem Framing
• Stakeholder Communication & Data Storytelling
• Attention to Detail & Reproducibility
• Collaboration & Ownership

Why join us?

• Build ML that runs on loyalty programs serving 400+ million members
• Own models end to end, from research through production
• Work on real modeling problems: churn, uplift, forecasting and program economics
• Collaborative, innovative environment with direct exposure to global brands
• Strong growth and learning opportunities within a rapidly expanding organization