Hello — I’m Shruti Dhamdhere

Data Scientist specializing in time-series analysis, NLP, and production-ready ML systems. Graduated with a M.S. in Data Architecture & Management at Northeastern University with experience building monitoring and forecasting systems, RAG pipelines, and data platform migrations.

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About

I am a Data Scientist with hands-on experience in time-series monitoring, NLP model fine-tuning, and data platform engineering. I enjoy turning noisy instrumented data into actionable insights and building robust pipelines for production. Graduated with a M.S. in Data Architecture and Management at Northeastern University (GPA: 3.8/4.0), and a Graduate Teaching Assistant for DAMG 7250 — Big Data Architecture and Governance.

Skills

Experience

Data Scientist — Northeastern University, Boston, MA

Jan 2024 – Aug 2025

  • Developed a time-series system-state monitoring framework classifying 4 operational states using 25 sensors with 10‑minute prediction intervals.
  • Performed sensor behavior analysis and identified a 10‑minute pre-transition window using temporal heatmaps and aligned sensor profiling.
  • Compared 1D/2D CNNs, CNN‑LSTM, XGBoost and Random Forest; ensembled models to improve robustness and achieved 97% accuracy while reducing boundary misclassification.

Data Analyst Co-op — Combined Jewish Philanthropies, Boston, MA

Sep 2024 – Dec 2024

  • Migrated 4M+ CRM records to Salesforce using SQL/Python with audit validations achieving 99% data integrity.
  • Built Power BI dashboards (DAX) to track ROI and fund utilization, supporting oversight of $12M+ annual budgets.

Research AI Engineer — IISER Kolkata

Apr 2023 – Jul 2023

  • Fine-tuned OpenAI GPT‑Davinci and NLLB models for low-resource language translation on an NVIDIA A100; improved translation BLEU to 51 through tuning.
  • Built NLP preprocessing pipelines using NLTK and Hugging Face; optimized for constrained-data settings.

Data Scientist — Shobi Group

Nov 2021 – Jul 2023

  • Analyzed 8–15M rows of time-stamped machine data to identify drift and instability in process parameters preceding quality failures.
  • Performed machine-level comparative analysis to isolate machines with higher variance and reduced investigation surface for engineers.
  • Delivered Python notebooks and diagnostic visualizations used in on-floor root‑cause reviews.

Data Analyst Co-op — Pyibar Private Limited

May 2020 – Apr 2021

  • Analyzed sales and logistics data with SQL & Excel; built dashboards tracking margins and repeat customers, improving operational efficiency by 10%.

Projects

Early Warning Analytics for Physical Systems

Analyzed multivariate sensor time-series from the NASA C‑MAPSS turbofan engine dataset to detect early drift and variance changes indicating gradual system degradation. Built detectors and visual diagnostics for early-warning signals.

Domain-Aware Question Answering (RAG)

Developed an end-to-end RAG pipeline combining semantic vector retrieval and LLMs to produce grounded, context-aware answers—reducing hallucinations versus standalone LLMs.

Additional public repositories from my GitHub (auto-loaded):

Education

Northeastern University — Boston, MA

M.S. Data Architecture and Management | GPA: 3.8/4.0 — Sep 2023 – Aug 2025

Graduate Teaching Assistant (DAMG 7250 — Big Data Architecture and Governance)

Pune University

B.Tech — Electronics & Telecommunication | GPA: 9.4/10 — Aug 2018 – May 2022

Contact

If you'd like to work together, feel free to email or call me. I'm open to research and industry opportunities in ML, data science, data engineering, and analytics.

Email: shrutidhamdhere789@gmail.com LinkedIn