▷ [3 Days Left] Data Scientist

3 weeks ago

Chennai, India Mindsprint Full time
We are seeking an experienced Senior Data Science Engineer to join our innovative team. As a Machine Learning and Generative AI Specialist, you will play a critical role in developing and deploying advanced ML models and algorithms to drive data-driven decision-making processes. Here are the key responsibilities and desired skills:

1. Algorithm Development:

- Design and implement machine learning algorithms for various applications, including natural language processing (NLP), recommendation systems, and predictive analytics.- Leverage your expertise in deep learning and generative AI to create innovative solutions.

2. Data Processing and Analysis:

- Collect, preprocess, and analyze large-scale datasets.- Apply statistical techniques and feature engineering to extract meaningful insights from data.

3. Model Training and Evaluation:

- Train and fine-tune ML models using Python and relevant libraries (e.g., TensorFlow, PyTorch).- Evaluate model performance using appropriate metrics and iterate to improve accuracy and efficiency.

4. Deployment and Monitoring:

- Deploy ML models to production environments (e.g., cloud platforms such as Azure, AWS, or GCP).- Monitor model performance, troubleshoot issues, and ensure robustness and reliability.

5. Collaboration and Communication:

- Collaborate with cross-functional teams, including data scientists, engineers, and product managers.- Communicate results and insights effectively to technical and non-technical stakeholders.

Desired Skills:

• Machine Learning: Strong knowledge of ML algorithms, including supervised and unsupervised learning.

• Generative AI: Experience with generative models (e.g., GANs, VAEs) and their applications.

• Python: Proficiency in Python for data analysis, model development, and scripting.

• Cloud Platforms: Hands-on experience with Azure, AWS, or GCP for model deployment and scalability.

• Natural Language Processing (NLP): Understanding of NLP techniques, sentiment analysis, and

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