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    Data Scientist - Bengaluru, India - Krishna Global Services Pvt. Ltd

    Krishna Global Services Pvt. Ltd
    Krishna Global Services Pvt. Ltd Bengaluru, India

    3 days ago

    Default job background
    Description

    AI/ML and predictive analytics, strong background in Data Science, expertise in Natural Language Processing (NLP).

    Data Science AI/ML.

    Must Have Skills AI/ML and predictive analytics, strong background in Data Science, expertise in Natural Language Processing (NLP).

    Location (Hybrid/WFO) Hybrid.

    Bangalore is preferred location.

    Alternate options can be Chennai or Hyderabad.

    - 7+ years of experience in AI/ML and predictive analytics.

    - Strong background in Data Science.

    - Expertise with Natural Language Processing (NLP).

    - Experience in large Language Model (Text generation, translation content summary, classification).

    - Working experience with Agile methodologies.

    - Understanding of Quality Assurance and Issue Management.

    - Proficiency in programming languages such as Python, coupled with experience in machine learning framework and cloud platforms.

    - Excellent analytical and problem-solving skills.

    - Automotive Domain experience would be an added advantage.

    Responsibilities :

    AI/ML Model Development :

    Design, develop, and deploy advanced machine learning models and algorithms to solve complex business problems.

    Utilize techniques such as supervised and unsupervised learning, deep learning, and ensemble methods.

    Predictive Analytics :

    Apply statistical and predictive modeling techniques to analyze large datasets and uncover trends, patterns, and correlations.

    Develop predictive models for forecasting, classification, clustering, and anomaly detection.

    Natural Language Processing (NLP) :

    Lead NLP projects to extract insights from textual data, including sentiment analysis, entity recognition, topic modeling, and text summarization.

    Implement NLP algorithms and techniques using libraries such as NLTK, spaCy, and TensorFlow.

    Data Exploration and Preprocessing :

    Clean, preprocess, and prepare data for analysis, ensuring data quality and integrity.

    Perform exploratory data analysis (EDA) to gain insights into data distributions, correlations, and outliers.

    Feature Engineering :

    Engineer features from structured and unstructured data sources to improve model performance and predictive accuracy.

    Select relevant features and perform dimensionality reduction techniques when necessary.

    Model Evaluation and Optimization :

    Evaluate model performance using appropriate metrics and validation techniques.

    Fine-tune models to optimize performance, scalability, and interpretability.

    Collaboration and Communication :

    Collaborate with cross-functional teams including data engineers, business analysts, and stakeholders to understand business requirements and translate them into actionable insights.

    Communicate findings and recommendations effectively through reports, presentations, and data visualizations.

    Research and Innovation :

    Stay updated on the latest advancements in AI/ML, NLP, and data science techniques.

    Explore new methodologies and tools to enhance analytical capabilities and drive innovation.

    Requirements :

    Bachelor's degree in Computer Science, Statistics, Mathematics, or related field.

    Advanced degree (Master's or Ph.D.) preferred. 7 to 10 years of experience in data science, with a focus on AI/ML, predictive analytics, and NLP.

    Strong proficiency in programming languages such as Python or R, with experience in data manipulation, analysis, and visualization libraries (e.g., pandas, NumPy, matplotlib, seaborn).

    Expertise in machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.

    Extensive experience with NLP frameworks and libraries such as NLTK, spaCy, Transformers, and BERT.

    Solid understanding of data preprocessing techniques, feature engineering, and model evaluation methodologies.

    Excellent problem-solving skills and analytical thinking, with the ability to translate business requirements into technical solutions.

    Strong communication and collaboration skills, with the ability to work effectively in a team environment and interact with stakeholders at all levels.

    Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark) is a plus.

    )
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