Data & AI

Architects KPI measurement models, cohort frameworks, and attribution dashboards to inform strategic decisions.

Constructs enterprise ontologies and knowledge graphs, linking disparate semantic entities for graph queries.

Architects distributed big data platforms and streaming engines (Spark, Kafka), scaling lakehouse infrastructure.

Builds text classification, named entity recognition, and semantic search pipelines using transformer models.

Applies supervised fine-tuning and RLHF alignment to language models, evaluating benchmark performance gains.

Architects multi-model LLM routing, prompt caching, and cost-efficient fallback layers for enterprise apps.

Builds classification and regression models, optimizing data preprocessing pipelines and model hyperparameters.

Automates machine learning deployment pipelines, continuous retraining triggers, and model registry governance.

Engineers production machine learning serving pipelines, automating model deployment and drift observability.

Engineers predictive features, trains machine learning models, and evaluates accuracy against validation metrics.

Designs reinforcement learning environments and reward functions, evaluating agent policy convergence metrics.

Optimizes PostgreSQL vacuuming, table partitioning, and GIN/btree indexes, delivering tuning configurations.

Architects retrieval-augmented generation (RAG) pipelines, tuning vector embeddings and chunking strategies.

Analyzes slow query logs and execution plans, recommending indexing fixes and SQL query performance rewrites.

Queries enterprise datasets with SQL, identifies statistical anomalies, and delivers structured analytical reports.

Develops business intelligence dashboards and cohort retention models, delivering operational KPI summaries.

Develops statistical hypothesis tests and predictive algorithms, turning complex data into actionable discoveries.

Transforms complex tabular data into intuitive interactive charts and dashboards tailored for executive clarity.

Monitors data ingestion latency, schemas, and pipeline failures, delivering data pipeline reliability assessments.

Consolidates siloed data feeds into unified single-source-of-truth tables, resolving entity resolution conflicts.

Builds automated ETL and ELT data pipelines, modeling warehouse schemas to ensure reliable data flow and integrity.

Designs automated scraping and document parsing pipelines that extract structured attributes from raw text.

Designs relational and NoSQL database schemas, defining indexing strategies and high-availability topologies.

Audits model training datasets for labeling errors and class imbalances, delivering data cleansing playbooks.

Integrates deep learning and foundation models into software systems, optimizing inference latency and pipelines.

Runs automated LLM benchmark suites, tests prompt iterations, and delivers empirical output evaluation notes.

Engineers high-fidelity prompts with structured output constraints, few-shot exemplars, and eval benchmarks.