ML / Data Science

ENTER; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Quantbot in Bengaluru, India seeks a machine learning engineer to design, implement, and evaluate ML models using Python, NumPy, Pandas, and Scikit-learn. You will preprocess data, engineer features, and validate models with robust evaluation strategies.

Knowledge of SQL, data visualization, and deployment practices is essential. The role may involve working with TensorFlow or PyTorch, cloud platforms, and containerized environments to scale models in production.

Qualifications

• Candidate should demonstrate strong Python and ML proficiency with practical experience in data preprocessing, feature engineering, and model evaluation.
• Solid understanding of statistics, probability, linear algebra, and calculus for ML modeling.
• Experience with supervised and unsupervised learning and common algorithms (regression, trees, ensemble methods, SVM, clustering).
• Ability to work with SQL and relational databases; familiarity with data visualization and EDA.
• Strong problem-solving and analytical abilities; ability to translate business needs into ML solutions.

Skills

Python

NumPy

Pandas

Scikit-learn

Matplotlib

Seaborn

Statistics

Probability

Linear Algebra

Calculus

ML: Supervised

ML: Unsupervised

Linear Regression

Logistic Regression

Decision Trees

Random Forest

SVM

K-Means

Gradient Boosting

Data Preprocessing

Feature Engineering

Model Evaluation

Cross-Validation

SQL

Data Visualization

Exploratory Data Analysis

Problem Solving

Analytical Skills

Tools

Docker

APIs

TensorFlow

PyTorch

AWS

Azure

GCP

Job description

Requirements

• Strong knowledge of Python and libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, and Seaborn
• Understanding of statistics, probability, linear algebra, and basic calculus
• Knowledge of supervised and unsupervised machine learning
• Understanding of algorithms such as Linear Regression, Logistic Regression, Decision Trees, Random Forest, SVM, K-Means, and Gradient Boosting
• Good understanding of data preprocessing, feature engineering, model evaluation, and cross-validation
• Knowledge of SQL and relational databases
• Familiarity with data visualization and exploratory data analysis
• Strong problem-solving and analytical skills

Preferred Skills

• Experience with Deep Learning using TensorFlow or PyTorch
• Knowledge of NLP, Computer Vision, or Generative AI/LLMs
• Familiarity with ML deployment and MLOps concepts
• Experience with cloud platforms such as AWS, Azure, or GCP
• Knowledge of Docker and APIs for deploying ML models
• Experience working with large datasets and production ML systems