Aditya Anand

Associate Consultant

Gurugram, Haryana, India2 yrs 11 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Spearheaded automation platform driving 20% revenue growth.
Developed advanced forecasting algorithms for oncology.
Built scalable cloud-native data pipelines for forecasting.

Stackforce AI infers this person is a Data Engineering and Analytics professional specializing in SaaS and AI-driven solutions.

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Skills

Core Skills

Data EngineeringForecastingArtificial Intelligence

Other Skills

AWSAdobe PhotoshopAmazon Web Services (AWS)ArduinoArtificial Intelligence (AI)BootstrapBusiness DevelopmentC (Programming Language)C++CI/CDChatbot DevelopmentCommunicationComputer ScienceDASHData Analysis

About

I'm a Data & Analytics professional with 2+ years of experience designing scalable data platforms and advanced forecasting solutions that drive business impact. My expertise lies in building automated data pipelines, deploying complex forecasting models, and collaborating with cross-functional teams to optimize data quality and improve operational efficiency. With a deep passion for data-driven decision-making, I specialize in transforming complex data into actionable business insights using tools like Python, SQL, AWS, and Terraform. I'm particularly intrigued by the ever-evolving fields of Artificial Intelligence, Machine Learning, and Data Science, and continuously seek to innovate and learn. Currently, as I advance in my career, I'm focused on leveraging my technical and strategic skills to contribute to impactful projects that support business growth and foster collaborative success.

Experience

2 yrs 11 mos

Total Experience

2 yrs 11 mos

Average Tenure

2 yrs 11 mos

Current Experience

Viscadia

3 roles

Associate Consultant

Promoted

Jan 2025 – Present · 1 yr 5 mos · Gurugram, Haryana, India

Spearheaded the delivery of Viscadia’s first forecasting automation platform, unlocking a multi-million
dollar client engagements and driving 20% revenue growth, scaling the development team from 3 to
15+ members accross verticals.
Developed an advanced forecasting algorithm that generated Excel formula-based outputs, improving
traceability and confidence over the earlier static-output engine. Designed cell-referencing logic for inputs
and outputs while supporting oncology-specific features like flow-based modeling and actuals incorporation.
Built cloud-native datapipelines using CI/CD based Lambdas, Glue, Athena and MS-SQL databases to
manage forecasting workflows and integrate with dashboard connectors such as Power BI, proprietary Excel
tools, and Gen-AI applications.
Consulted on development and deployment of a React-based Excel Add-in interface and web-based
governance portal, providing architectural guidance, design input, and technical oversight.
Initiated GenAI integration by developing a RAG-based chatbot prototype using Bedrock Agents, enabling document-level querying across client portfolios.
Built and scaled the product development team by mentoring junior engineers, conducting 20+ Python
training workshops for new hires, and leading 10+ inte

Data EngineeringAmazon Web Services (AWS)Python (Programming Language)SQLGen AIForecasting

Associate

Jul 2023 – Jan 2025 · 1 yr 6 mos · Gurugram, Haryana, India

Initiated Viscadia’s tech product journey by designing proprietary Python packages to automate client
forecasting processes, analyzing statistical models, deriving key features, and building modular systems to
mine data, compute forecasts, and generate outputs dashboards—implemented using robust design patterns
such as Singleton and Context Object.
Engineered a Risk Analytics module featuring Monte Carlo simulations, sensitivity analysis, and
scenario comparison, leveraging the modular forecast generation engine and parallel processing to
deliver high-speed, large-scale scenario analysis.
Built the platform’s foundational AWS infrastructure using Terraform, including secure VPCs, ECS
services, Lambda functions, Cognito , and S3, adapting infrastructure across client-owned accounts and
shared environments.
Collaborated with external AWS consultants during initial advisory phases, then led internal efforts to scale
infrastructure into a repeatable, multi-client, production-grade setup.