Data Scientist

Codefeast; Meerut; Hybrid; INR 800,000 - 1,400,000; Full time

Job summary

Codefeast is seeking an experienced Data Scientist to support AI training, data analysis, and model-evaluation projects in Meerut, India. You will analyse structured and unstructured datasets, evaluate AI-generated outputs for quality, and develop benchmarks and scoring criteria.

The role requires hands-on experience with Python, SQL, and ML concepts, along with data cleaning, feature engineering, and model evaluation. Preference for familiarity with AI training and visualization tools.

Qualifications

• 4+ years of professional experience in Data Science, Machine Learning, Data Analytics, or a related field.
• Strong proficiency in Python and SQL.
• Strong understanding of statistics, probability, and machine-learning concepts.
• Hands-on experience with Pandas, NumPy, SciPy, and Scikit-learn.
• Experience with data cleaning, preprocessing, feature engineering, and model evaluation.

Responsibilities

• Analyse large structured and unstructured datasets.
• Evaluate AI/ML model outputs for quality, accuracy, and consistency.
• Develop and apply evaluation criteria, benchmarks, and scoring frameworks
• Identify model errors, edge cases, biases, and data-quality issues.
• Perform data cleaning, validation, transformation, and feature analysis.

Skills

Python

SQL

Pandas

NumPy

SciPy

Scikit-learn

Statistics

ML concepts

Data cleaning

Feature engineering

Model evaluation

Tools

PyTorch

TensorFlow

Hugging Face

Jupyter

Power BI

Tableau

Matplotlib

Job description

We are looking for an experienced Data Scientist to support AI training, data analysis, and model-evaluation projects. The role involves analysing structured and unstructured datasets, evaluating AI-generated outputs, identifying model errors, and creating reliable benchmarks and evaluation criteria.

Responsibilities:

• Analyse large structured and unstructured datasets.
• Evaluate AI/ML model outputs for quality, accuracy, and consistency.
• Develop and apply evaluation criteria, benchmarks, and scoring frameworks
• Identify model errors, edge cases, biases, and data-quality issues.
• Perform data cleaning, validation, transformation, and feature analysis.

Requirements:

• 4+ years of professional experience in Data Science, Machine Learning, Data Analytics, or a related field.
• Strong proficiency in Python and SQL.
• Strong understanding of statistics, probability, and machine-learning concepts.
• Hands-on experience with Pandas, NumPy, SciPy, and Scikit-learn.
• Experience with data cleaning, preprocessing, feature engineering, and model evaluation.

Preferred Skills:

• Experience with AI Training, LLM Evaluation, Prompt Evaluation, RLHF, or benchmark creation.
• Familiarity with PyTorch, TensorFlow, Hugging Face, or Jupyter.
• Experience with visualisation tools such as Power BI, Tableau, Matplotlib, or similar.
• Exposure to cloud platforms, MLOps, or data pipelines is an advantage.