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Urgent! Data Scientist - Machine Learning Engineering Job Opening In India, India – Now Hiring Brainhunter Recruiting (India) Private Limited
<p><p><b>Description : </b> We are seeking a highly skilled and innovative Data Scientist with strong ML Engineering capabilities to design, develop, and deploy advanced machine learning models that drive actionable business insights.<br/><br/> This role bridges the gap between data science research and machine learning production deployment, requiring expertise in statistical modeling, data analysis, algorithm development, and MLOps.<br/><br/>The ideal candidate will work collaboratively with cross-functional teams to build scalable, high-performance machine learning systems that power intelligent business solutions.<br/><br/><b>Key Responsibilities : </b><br/><br/><b>Machine Learning & Model Development : </b><br/><br/>- Design, build, and train machine learning models for predictive analytics, classification, clustering, NLP, recommendation systems, or computer vision applications.<br/><br/>- Research and implement state-of-the-art algorithms and techniques in supervised, unsupervised, and reinforcement learning.<br/><br/>- Conduct feature engineering, model evaluation, and hyperparameter optimization to enhance performance.<br/><br/>- Implement best practices for model reproducibility, versioning, and validation.<br/><br/><b>Data Engineering & Pipeline Development : </b><br/><br/>- Build and maintain robust data pipelines for data ingestion, cleaning, transformation, and feature extraction using frameworks such as Apache Spark, Airflow, or Kedro.<br/><br/>- Collaborate with data engineers to ensure data quality, integrity, and availability across various sources and environments.<br/><br/>- Work with structured, semi-structured, and unstructured data, including large-scale datasets.<br/><br/><b>MLOps & Deployment : </b><br/><br/>- Package and deploy ML models into production environments using tools such as Docker, Kubernetes, TensorFlow Serving, or SageMaker.<br/><br/>- Monitor model performance post-deployment, detect model drift, and retrain models as necessary.<br/><br/>- Automate ML workflows (training, testing, deployment, monitoring) through CI/CD pipelines.<br/><br/>- Integrate machine learning outputs into real-time or batch systems using APIs or microservices.<br/><br/><b>Data Analysis & Business Insights : </b><br/><br/>- Perform exploratory data analysis (EDA) to identify patterns, correlations, and business opportunities.<br/><br/>- Collaborate with business stakeholders to understand challenges and translate them into machine learning problems.<br/><br/>- Communicate results and insights clearly using visualizations, dashboards, and presentations.<br/><br/><b>Collaboration & Continuous Improvement : </b><br/><br/>- Work closely with data engineers, product managers, and software developers to ensure end-to-end solution delivery.<br/><br/>- Stay abreast of advancements in AI/ML technologies, frameworks, and tools, integrating them into ongoing projects.<br/><br/>- Contribute to knowledge sharing, documentation, and mentoring of junior team members.<br/><br/><b>Required Qualifications & Skills : </b><br/><br/>- Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, Statistics, or a related field.<br/><br/>- 2+ years of hands-on experience in machine learning model development and deployment.<br/><br/>- Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost.<br/><br/>- Strong understanding of data structures, algorithms, and software engineering principles.<br/><br/>- Experience with data manipulation and analysis tools (Pandas, NumPy, SQL, Spark).<br/><br/>- Solid understanding of statistical methods, probability, and mathematical modeling.<br/><br/>- Proven experience in building and deploying models using MLOps frameworks.<br/><br/>- Familiarity with cloud ML services (AWS Sagemaker, Azure ML, GCP AI Platform).<br/><br/>- Hands-on experience in using Git, CI/CD tools, and containerization technologies.<br/><br/>- Excellent problem-solving skills, analytical thinking, and attention to detail.<br/><br/><b>Preferred Skills : </b><br/><br/>- Experience with deep learning architectures (CNNs, RNNs, Transformers).<br/><br/>- Familiarity with NLP frameworks (spaCy, Hugging Face Transformers, NLTK).<br/><br/>- Experience with data visualization tools such as Power BI, Tableau, or Plotly.<br/><br/>- Knowledge of feature store management and model monitoring tools.<br/><br/>- Experience in A/B testing and model interpretability (SHAP, LIME).<br/><br/>- Exposure to big data ecosystems (Hadoop, Databricks, Snowflake)</p><br/></p> (ref:hirist.tech)
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Unlock Your Data Scientist Potential: Insight & Career Growth Guide
Real-time Data Scientist Jobs Trends in India, India (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for Data Scientist in India, India using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 140644 jobs in India and 9675 jobs in India. This comprehensive analysis highlights market share and opportunities for professionals in Data Scientist roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! Brainhunter Recruiting (India) Private Limited is currently hiring and seeking a Data Scientist Machine Learning Engineering to join their team. Feel free to download the job details.
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An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Brainhunter Recruiting (India) Private Limited adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a Data Scientist Machine Learning Engineering Jobs India varies, but the pay scale is rated "Standard" in India. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for Data Scientist Machine Learning Engineering typically include Mathematical Science Occupations and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
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