Aryan Ringshia

Data Scientist

Ann Arbor, Michigan, United States3 yrs 3 mos experience

Key Highlights

Improved sales forecasting accuracy by 6%.
Developed risk classification model for construction projects.
Led workshops and lectures on AI/ML topics.

Stackforce AI infers this person is a Data Scientist with expertise in predictive modeling and data analysis across various industries.

Contact

Skills

Core Skills

Data ScienceMachine LearningData AnalysisData EngineeringNlp

Other Skills

AWS GlueAWS LambdaAWS SageMakerAmazon Web Services (AWS)Analytical SkillsAzure DatabricksC (Programming Language)CommunicationComputer VisionConstruction ManagementData VisualizationDemand ForecastingIBM SPSS StatisticsJavaMLOps

About

Results-driven Data Scientist with hands-on experience in predictive modeling and data visualization. As a Data Scientist at Barton Malow, I use historical, financial, and schedule datasets to flag at-risk projects and streamline operations. At TransOrg Analytics, I focused on sales forecasting, improving accuracy by 6% for retail clients. Passionate about leveraging actionable insights to drive decision-making and enhance operations.

Experience

3 yrs 3 mos

Total Experience

1 yr 10 mos

Average Tenure

1 yr 5 mos

Current Experience

Barton malow

2 roles

Data Scientist II

Jan 2025 – Present · 1 yr 5 mos · Southfield, Michigan, United States · Hybrid

Data Scientist I Intern

May 2024 – Dec 2024 · 7 mos · Southfield, Michigan, United States · Hybrid

Architected risk classification model using PySpark to predict the success or failure of ongoing construction projects and optimize project management.
Visualized insights from historical, financial, and schedule datasets on PowerBI dashboards and created medallion architecture using Delta Live Tables.
Revamped data dictionaries to establish consistency and streamline data usage across Financial, Accounting, and Strategy departments, improving data-driven strategic planning.
Refined project status report groupings via Dynamic Time Warping and deployed models in Azure Databricks.

Azure DatabricksPySparkPython (Programming Language)SQLData ScienceMachine Learning

University of michigan

Instructional Assistant

Sep 2024 – Dec 2024 · 3 mos · Ann Arbor, Michigan, United States

Course: N218: Applied Statistics.

University of michigan

Instructional Assistant

Sep 2023 – Dec 2023 · 3 mos · Ann Arbor, Michigan, United States · On-site

Courses: N218: Applied Statistics & N142: Nursing Seminar

Communication

Dj init.ai

2 roles

Senior Mentor

Promoted

Jul 2022 – Jun 2023 · 11 mos

Guided team of 12 junior mentors for venturing into subdomains of AIML through individual projects.
Supervised 25 lectures for juniors on Data Analysis, Neural Networks and Machine Learning algorithms.
Organized workshops to provide opportunities for junior members to apply AI/ML knowledge to real-world challenges.
Held lecture series on Transfer Learning for Deep Learning covering AlexNet, ResNet and VGG model.

Data AnalysisMachine Learning AlgorithmsCommunicationData Science

Junior Mentor

Jul 2021 – Jun 2022 · 11 mos

Worked on research and industry-oriented projects to advance in domain of AIML with guidance from seniors.
Held weekly lectures to teach AI and its fundamentals to sophomore students.

Data AnalysisMachine Learning AlgorithmsCommunicationData Science

Dwarkadas j. sanghvi college of engineering

Teaching Assistant

Jun 2022 – Jul 2022 · 1 mo · Mumbai, Maharashtra, India

Course: Machine Learning - II, DJ19DSC501 - Worked under the Head of the Department of Data Science.
Designed ML laboratory experiments for undergraduate students, aligning with the course curriculum and learning objectives.
Formulated teacher’s manual for these experiments that provided solutions and supplemental material covering background knowledge and principles.

Data ScienceData AnalysisMachine Learning AlgorithmsPython (Programming Language)Communication

Transorg analytics

Data Science Intern

Jun 2021 – Jan 2022 · 7 mos

Implemented Neural Network Forecasting using SageMaker DeepAR with Dynamic Dashboard hosted on AWS QuickSight offering customer analytics – improved forecast accuracy by 6% on average in client’s sales districts.
Developed automated AWS ETL pipeline using serverless paradigms – Glue, Lambda – along with time series demand forecasting on AWS Forecast to meet the analytics needs of FMCG client.
Built Chatbot for hosting on client’s website incorporating Sentiment analysis and Topic modeling.
Won company hackathon in December 2021 working as part of a team on Recommendation Engine for hospitality industry client involving extensive feature engineering and delivering a Customer 360 Dashboard.
Researched Serverless Dynamic Pricing Strategy on AWS Kinesis.

TableauData ScienceData AnalysisNatural Language Processing (NLP)Machine LearningAWS Glue+7