Shubham Yedekar

About Shubham Yedekar

Data Scientist | ML & AI Engineer Passionate about building futuristic AI solutions using machine learning, deep learning, and advanced analytics to solve complex business challenges. Skilled in Python, R, SQL, AWS, GCP, with expertise in NLP, deep learning (CNNs, RNNs, Transformers), time-series forecasting, and MLOps. I specialize in scalable ML systems, automation, and real-time decision intelligence, combining statistical modeling, A/B testing, and causal inference with cutting-edge AI. Collaborative and innovation-driven, I thrive on turning raw data into impactful insights that power the future.

Experience

1. Data Scientist

   Community Dreams Foundation

   Aug 2025 — Present · US

   Gather and collect structured and unstructured data from various sources- Clean and preprocess the data to ensure quality and accuracy- Analyze data to discover patterns, correlations, and trends- Use statistical tools and techniques to summarize the data and extract meaningful insights- Develop predictive models and machine learning algorithms to solve business problems- Select appropriate modeling techniques and tools based on the data and the problem at hand- Create visualizations and dashboards to present data insights in an understandable and actionablemanner- Design and conduct experiments to test hypotheses and validate models- Analyze results to determine the effectiveness of different strategies or interventions- Work closely with cross-functional teams, including business analysts, engineers, and productmanagers, to understand business requirements and objectives- Communicate findings and recommendations to both technical and non-technical stakeholders- Implement models into production environments and ensure they perform as expected- Monitor model performance over time and make necessary adjustments to improve accuracy andreliability- Stay updated with the latest trends, tools, and technologies in data science- Continuously improve skills in programming languages like Python, R, SQL, and tools likeTensorFlow, PyTorch, or Hadoop- Ensure that data is handled ethically, respecting privacy, confidentiality, and compliance withregulations such as GDPR- Document methodologies, processes, and findings to ensure reproducibility and transparency indata science projects.

Education

• University of Connecticut School of Business

  Master's degree, Data science

• Bharati Vidyapeeth College of Engineering, Navi Mumbai

  Bachelor of Engineering - BE, Electrical, Electronic and Communications Engineering Technology/Technician

  2017 — 2021