divya Reddy

Open to

Bangalore

Work style

hybrid

Availability

Available in 15 days

Contact details — on requestProof of Work — on request

Experience

Data Scientist

Landmark Group Data Labs · Apr 2022 – Present

Not yet confirmed

Partnered with BRMs and cross-functional teams (Data Engineering, Platform Engineering, Business Analysts) to translate business requirements into scalable data science solutions, identifying process improvement opportunities through data-driven analysis and Continuous Improvement (CI) methodologies to deliver measurable business value.
Led regular forecast review sessions with business stakeholders and planners, presenting forecast accuracy results and troubleshooting variances to support customer-facing decision-making and continuous process improvement.
Built scalable analytical datasets using PySpark, SQL, and Azure Databricks by integrating sales, inventory, promotions, and seasonality data across 10M+ records, enabling feature engineering and improving forecasting accuracy.
Developed and deployed 16,000+ ML/DL forecasting models monthly across 4,000+ SKUs using regression, tree-based models, gradient boosting (XGBoost), PyTorch-based neural forecasting (NHITS), ARIMA, SARIMA, and Prophet, reducing WMAPE below 20% and lowering stock-outs/overstock by 10% through root-cause variance analysis.
Applied statistical techniques including exploratory data analysis, hypothesis testing, backtesting, model validation, Design of Experiments (DOE), and hyperparameter tuning to optimize model performance and quantify forecast uncertainty.
Owned the end-to-end model lifecycle by designing reusable, versioned, and reproducible MLOps pipelines using MLflow, Git, Azure Databricks, and Feature Store for experiment tracking, backtesting, model deployment, performance monitoring, data drift detection, and automated retraining, reducing production runtime by 50%.
Built Pulse Inventory Insights, an LLM-powered retail analytics solution using PySpark and GPT-based models to generate automated inventory health summaries and planner-friendly business insights across 4,000+ SKUs.

Skills 0 proven through work

Also works with

Processing Pipeline OptimizationClient FocusBusiness AcumenSpeaking ClearlyPlain-Language SimplificationAdaptabilityWork Planning and PrioritizationCross-Departmental CoordinationHypothesis-Driven ExperimentationData ConsumptionBefore-and-After Impact MeasurementGenerative AI ApplicationData UnderstandingProblem SolvingAI Solution ImplementationAI Hallucination DetectionPrompt EngineeringInventory AnalysisBusiness IntelligenceAutomated Summarization SystemsLarge Language Model ConceptsRetail AnalyticsLLM Application IntegrationScalable System DesignVersion Control with GitHubETL Pipeline DevelopmentDataset VersioningMLflow UsageMachine Learning Model DeploymentModel Training ExecutionData PreprocessingMLOps ImplementationML Experiment TrackingDeep LearningMachine Learning ApplicationModel Selection Trade-Off AnalysisRoot Cause AnalysisKPI AnalysisModel Error AnalysisForecastingFeature EngineeringData ValidationTabular Data Cleaning & ValidationData Unification and NormalizationData-Driven RecommendationsProcess ImprovementData Architecture DesignExploratory Data Analysis (EDA)Data EngineeringDatabricks UsageSpark SQLPySpark

Proof of Work

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Education

Master's, Data Science and Machine Learning

PES University, Bangalore · 2020 — 2022

Bachelor of Engineering, Electronics and Communication

New Horizon College of Engineering · 2013 — 2017

Contact details

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