Gen AI/ML Engineer -Data Scientist

Overview

On Site
$80,000+
Full Time

Skills

Gen AI
ML
Data Science
Python
SQL
Statistics
Tableau & Power BI
Big Data Wrangling
Data Analysis
Big Data
AWS & Azure
DSA
Deep Learning
NLP

Job Details

Data Science:
  • Programming:
    Proficiency in Python, R, and SQL is essential for data manipulation, analysis, and model building.
  • Statistics:
    A strong foundation in statistics, probability, and linear algebra is required for understanding data distributions, performing statistical tests, and developing models.
  • Machine Learning:
    Knowledge of various machine learning algorithms (regression, classification, clustering), model evaluation, and feature engineering is crucial.
  • Data Visualization:
    Ability to create effective visualizations (e.g., using Tableau, Power BI, Matplotlib) to communicate insights and trends in data.
  • Data Wrangling:
    Skills in data cleaning, transformation, and preparation are necessary to handle messy and incomplete data.
  • Data Analysis:
    Ability to interpret data, identify patterns, and draw meaningful conclusions.
  • Big Data:
    Experience with technologies like Spark and Hadoop for handling large datasets.
  • Cloud Computing:
    Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) for storing, processing, and deploying models.
AI:
  • Programming:
    Strong programming skills, particularly in languages like Python and C++, are required for building and deploying AI models.
  • Machine Learning:
    In-depth knowledge of machine learning algorithms, model training, and evaluation is essential.
  • Deep Learning:
    Understanding of neural networks, deep learning frameworks (e.g., TensorFlow, PyTorch), and their applications in computer vision and natural language processing.
  • Computer Vision:
    Skills in image recognition, object detection, and other computer vision tasks.
  • Natural Language Processing (NLP):
    Understanding of text processing, language modeling, and speech recognition.
  • Big Data:
    Ability to work with large datasets and utilize technologies like Spark and Hadoop for data analysis and model training.
Int
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