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Vetted Statistical Analysis Professionals
Pre-screened and vetted.
Yili Jin
Intern Software Engineer specializing in data systems and machine learning
“Internship experience at TikTok and nCino, with hands-on work spanning production Python data pipelines, recommendation-system feature workflows, Salesforce Apex automation, and flaky UI automation for a live stock recommendation platform. Stands out for a reliability-focused approach: anticipating failure modes, instrumenting observability, and turning ambiguous business processes into maintainable automated systems.”
Senior Healthcare Data & Program Manager specializing in AI data annotation
Senior Python AI/ML Engineer specializing in MLOps, data engineering, and LLM applications
Mid-level Product Manager and Business Analyst specializing in data-driven strategy
Mid-level AI & Machine Learning Engineer specializing in production ML and LLM applications
Executive product and technology leader specializing in HR Tech and FinTech
Mid-level Machine Learning Engineer specializing in GenAI, LLM agents, and MLOps
Principal AI Platform Architect specializing in agentic AI and enterprise LLM infrastructure
Mid-level AI/ML Engineer specializing in GenAI, MLOps, and big data on cloud platforms
Senior Data Engineer specializing in cloud-scale data pipelines and legal data systems
Principal Machine Learning Architect specializing in AI platforms and data science
Senior Data Analyst specializing in healthcare and financial analytics
Senior Business Analyst specializing in data analytics and business intelligence
Mid-level analyst and venture associate specializing in litigation analytics and investing
Senior Data Engineer specializing in cloud-scale pipelines and legal data utilities
Executive IT & Software Development Leader specializing in cloud-native transformation and trading platforms
Surya Vardhan
Junior Operations Data Analyst specializing in KPI dashboards and SLA reporting
“Manufacturing/quality-focused professional with experience at Sikorsky Aerospace supporting aircraft parts production for clients such as Boeing and Cobham. Drove data-driven process improvements (cleaned/visualized production data) and redesigned material usage to cut delays by ~20% and reduce waste, while coordinating across production, inspection, QC, and delivery readiness.”
Chitra Uppalapati
Entry-level Software Engineer specializing in full-stack and machine learning applications
“Built production Python data integrations and dashboard automation for incident analytics, with a strong focus on data quality, observability, and reliability for leadership-facing reporting. Also translated an ambiguous manual creator evaluation process at startup Spring into an automated predictive scoring feature, showing a blend of backend data engineering, test automation, and cross-functional product thinking.”
Sumanth Salluri
Mid-level Business Data Analyst specializing in Financial Services and Healthcare analytics
“Full-stack engineer (~4 years) who has owned and shipped customer-facing SaaS onboarding and a role-based real-time analytics dashboard using TypeScript/React with a modular backend. Experienced in microservices with RabbitMQ and strong observability practices (correlation IDs, structured logging, queue metrics), and built an internal deployment tracker integrated with CI/CD that replaced manual spreadsheet/Slack processes.”
Nikita Vivek Kolhe
Junior Data & Machine Learning Engineer specializing in MLOps and NLP
“ML/LLM practitioner with production experience building a healthcare review sentiment pipeline (RateMDs) using Hugging Face Transformers plus a LangChain+FAISS RAG layer for interactive querying. Also led orchestration-driven optimization of Nike’s Fusion ETL pipeline, improving runtime efficiency by 20%, and has experience translating ML outputs into Tableau dashboards for non-technical healthcare stakeholders (e.g., readmission risk).”
Asad Mohammed
Mid-level AI/ML Engineer specializing in generative AI and intelligent automation
“Backend-focused AI engineer with enterprise experience building startup-style internal products at JPMorgan Chase. He helped create an AI-powered financial research platform for analysts, leading retrieval and multi-agent orchestration work that cut research prep from hours to under 20 minutes while scaling across large volumes of SEC filings and earnings transcripts.”