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Honeywell International · Bengaluru, Karnataka, India

# Advanced Data Scientist

Bengaluru, Karnataka, India On-site Data & Analytics 

Listed on Honeywell International’s official careers site. Posted September 8, 2026. Check that it is still open and apply there.
[Apply on Honeywell International’s careers site →](https://ibqbjb.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/157101)

[OpenNash Jobs](https://jobs.opennash.com/) / [Honeywell International](https://jobs.opennash.com/companies/honeywell-international/) / Advanced Data Scientist

## Job description

### Key Responsibilities

Mathematical Formulation: Translate ambiguous business problems into mathematically sound framework objectives and optimisation targets.

### Production-Grade Engineering

Write clean, modular, and maintainable code using production-level design patterns to scale mathematical models.

### Big Data Processing

Design and manage scalable data pipelines to process massive datasets efficiently for model training and inference.

### Deep Learning & Vision Development

Build, train, and fine-tune complex neural networks across text, audio, and visual modalities.

### Cloud Deployment

Architect and deploy models to cloud environments, leveraging distributed computing and robust cloud infrastructure.

### Required Technical Skills & Competencies
- Tooling, Libraries & Software Engineering Core Language: Advanced proficiency in Python with a strict adherence to Object-Oriented Programming (OOP) principles, clean coding standards, and design patterns.

### Machine Learning Libraries

Advanced proficiency in scikit-learn (sklearn) for data preprocessing, feature engineering, and baseline modelling.

### Deep Learning Frameworks

Core expertise in PyTorch (preferred) or TensorFlow for building, customizing, and training deep neural networks from scratch.

### Big Data Ecosystem

Experience with Apache Spark (PySpark) and the Hadoop Ecosystem (HDFS, Hive, MapReduce) for handling, transforming, and querying large-scale distributed datasets.

### Cloud Architecture

Experience building and deploying scalable machine learning applications on major cloud platforms ( AWS, Azure, or GCP).

### Core Mathematics & First-Principles ML Foundational Math
- Solid foundation in Linear Algebra (eigenvalues, SVD, matrix decompositions), Multivariable Calculus (partial derivatives, gradients, Jacobians), and Probability Theory (Bayesian inference, probability distributions, expectation maximization).

### Machine Learning

In-depth understanding of standard Machine Learning algorithms (Trees, Boosting, SVMs, GMMs) with the ability to explain the underlying loss functions and optimizations mathematically.

### Deep Foundations

Thorough understanding of Multi-Layer Perceptrons (MLPs), mathematical derivation of backpropagation, hyperparameter initialization strategies (Xavier, He), optimization variants (Adam, RMSProp), and advanced regularization techniques (L1/L2, Dropout, Batch Normalization).

### Advanced Natural Language Processing (NLP) Sequential Networks
- Hands-on experience with sequence modeling, including Word Embeddings (Word2Vec, FastText), RNNs, LSTMs, and GRUs.

### Transformer Ecosystem

Deep structural knowledge of the Transformer architecture (Self-Attention math, Multi-Head mechanisms).

### Pre-trained NLP Models

Experience implementing and fine-tuning encoder-only (BERT, RoBERTa) and decoder-only (GPT series) architectures.

### Computer Vision (CV) & Document AI Spatial Networks
- Deep understanding of Convolutional Neural Networks (CNNs), feature map mathematics, pooling operations, and advanced CV backbones.

### OCR & Document Processing

Proven track record building or customizing Optical Character Recognition (OCR) systems for complex text extraction pipelines.

### Vision Transformers

Familiarity with the adaptation of attention mechanics to visual tasks (ViTs, Swin Transformers). Education & Experience

## Qualifications

### Education

Bachelor’s, Master's, or Ph.D. in a highly quantitative field (Mathematics, Statistics, Econometrics, Computer Science, Physics, or Operations Research).

### Experience

4 to 6 years of industry experience working as a Data Scientist or Machine Learning Engineer with a portfolio of complex multimodal projects.

## At a glance
- Posted by the employer: Sep 8, 2026
- First seen by OpenNash: Oct 11, 2026
- Last checked: Oct 18, 2026
- Listed for: 40 days
- Location: Bengaluru, Karnataka, India
- Work arrangement: On-site[Apply on Honeywell International’s careers site →](https://ibqbjb.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/157101)

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