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Nimanshi Jha 

Data Scientist 

Phone: (+49) 15752854259

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Email:
nimanshi9j@gmail.com | nimanshi.jha@pwc.com

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Address:

Frankfurt am Main, Germany

LinkedIn | Xing | Twitter | Kaggle | GitHub

In a Nutshell

Nimanshi is a Data Scientist in the Data & Analytics team in Germany, with a passion for driving data-driven insights and solutions, bringing a diverse range of skill set and valuable experience. With a background in machine learning, data science and engineering, Nimanshi possesses a strong foundation in the field. Through her professional journey, Nimanshi has demonstrated ability to build end to end MLOps Pipelines from Scratch. Her expertise in automation, data quality, and management has proven instrumental in optimizing processes and ensuring accurate and reliable results. Driven by a commitment to continuous learning, Nimanshi stays at the forefront of the field, actively seeking out the latest advancements and emerging technologies.

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Expertise

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Work Experience

05/2023 – Present
Frankfurt, Germany 

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04/2022 – 09/2022
Frankfurt, Germany 

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10/2022 – 03/2023
Bingen, Germany 

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PwC Deutschland | Data Scientist

Team : CDO - Product and Technology

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  • Azure Data Factory & Pipeline Development: Engineered robust data pipelines within Azure Data Factory to streamline the cleaning and analysis of travel emissions data from various booking platforms. Implemented Python code to calculate emissions, ensuring precise and reliable results across multiple travel categories (hotels, taxis, cars, etc.).

  • Leadership & Data Quality Initiative: Led the data quality team, overseeing the data upload process and ensuring stringent QA protocols were met. Directed the team in managing workflows, including training and supervising interns, to maintain high standards of accuracy and reliability in data management.

  • Strategic Collaboration: Partnered with senior leadership to develop an in-depth white paper that explored cutting-edge applications of generative AI for sustainability initiatives, reflecting strategic thinking and high-level stakeholder engagement on transformative projects.

PwC Deutschland 

Team : Sustainability

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  • Expertise in EU Sustainability Frameworks: Specialized in EU Taxonomy, LKSG, SFDR, and Pathway to Paris, ensuring compliance with evolving sustainability regulations and aligning corporate initiatives with legal mandates.

  • Automated PDF Management System: Developed Python scripts to automate PDF handling, reducing processing time by 40% and boosting accuracy by 70%, streamlining document processing for sustainability reporting.

  • Data Quality & Optimization Dashboards: Created dashboards to monitor data quality metrics, enabling real-time tracking and process optimization, driving improvements in sustainability reporting and compliance efficiency.

Suewag Energie AG (Syna) | Working Student 

Team: Digital Process and Data 

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  • Implemented end-to-end Machine Learning Operations for Predictive Maintenance of Power Cables,encompassing data preprocessing, model development, deployment, monitoring, and retraining stages.

  • Conducted thorough analysis, cleaning, encoding, and interpretation of data. Leveraged SQL to extract necessary spatial data from the database, employing Object-Oriented Programming (OOP) for optimized code.

  • Developed an Automated Data Profiling module to expedite analysis, facilitating the swift generation of detailed reports.

Technical University of Applied Science Bingen | Thesis - Similarity Search with Vector Embeddings for PDF Documents 

  • Conducted an empirical investigation into the transformation of PDF documents into vector embeddings through the utilization of RNN, LSA, and Doc2Vec. Evaluated the effectiveness of these embeddings in downstream tasks, with a focus on category prediction. Implemented a systematic pipeline for PDF preprocessing, content extraction, embedding generation and ML model evaluation, thereby contributing valuable insights to the field of document analysis and classification through the numerical representation of PDF content.

Technical University of Applied Science Bingen | Major Project - Serverless FinOps Reporting with Evoila GmbH

  • Led a project as a Product Owner and Developer in Scrum Agile, setting
    up a serverless environment for cost data storage and analysis,
    implementing Lambda functions, API gateway, and automated reporting.

04/2022 – 09/2023
Bingen, Germany 

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01/2019 – 05/2019
Chennai, India 

SRM Institute of Science and Technology | Thesis - Comparaive Study on Clustering Validation Indices 

  • Presented a detailed Report on Literature Survey on Factors affecting Clustering Indices, Cluster Validity Measurement Techniques. Studied useful metrics to evaluate cluster cohesion, purity, & accuracy. Extensively compared several cluster validity indices for both artificial and real-life datasets.

10/2022 – 03/2023
Frankfurt, Germany 

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06/2018 – 06/2018
India 

Persistent Systems | Academic Intern

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Project: Data Connector

  • Collaborated on optimizing customer database management by writing interface to fetch user data, connecting to the database, and analyzing data using Python and SQL.

Education 

IGCHE Dual Degree

Technische Hochschule Bingen| Bachelors Informatik | Bingen (Germany) | Graduation February 2023

SRM Institute of Science and Technology | BTech Computer Science Engineering | Chennai (India)

 

Relevant Coursework: Machine Learning, Big Data, and Data Engineering, Python, Agile Project Management, Discrete Mathematics, Probability, and Queuing Theory, Advanced Calculus and Complex Analysis, Data Structures, Object-Oriented Programming, Algorithm Design and Analysis, Database management Systems, Cloud Computing, Digital Image Processing

Generative AI Nanodegree

Udacity | 06/2024 - 10/2024

Gained hands-on experience in Generative AI techniques, including fine-tuning foundation models using methods like Low-Rank Adaptation (LoRA) and Parameter-Efficient Fine-Tuning (PEFT) with tools such as Hugging Face and PyTorch. Developed custom chatbots using retrieval-augmented generation (RAG), combining semantic search with large language models for more accurate, context-aware interactions. Additionally,Explored image generation with Stable Diffusion, including inpainting to modify images based on user input.Worked on generative AI solutions using OpenAI APIs, vector databases, and semantic search, creating prototypes like a tool that transforms real estate listings into customized narratives for enhanced user engagement.​

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COURSES AND CERTIFICATIONS

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  • DSH Certificate: DSH 2 - B2-C1 Niveau, Goethe Universität Frankfurt [12/2021]

  • Deeplearning.AI Coursera – Neural Network and Deep Learning, Introduction to TensorFlow for AI, ML & DL, Convolutional Neural Networks in TensorFlow, Sequences, Time-Series, and Prediction

  • Kaizen Robotics Lema Labs: Certificate by IIT Madras und Hasura - 8 weeks Hands-On workshop 

  • Ideathon Presentation - Papientrega 2.0: medical assistant

  • Semi-Colon 3.0: Coding Competition - Semi-Colon 3.0(round 2) - ITA SRM IST

  • Virtual Reality Workshop: Organized by EEEA SRMIST & Robocart ICON (National Level Technical Fest)

LANGUAGE SKILLS : English (Native Language) | German (C1/Fluent) 

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