Data Dynamics - Data Scientist - NLP/Deep Learning (4-5 yrs)

Objective of this role :

- Collaborate with product design and engineering teams to develop an understanding of needs.

- Research and devise innovative statistical models for data analysis.

- Build innovative models and integrate them in our product.

- Communicate findings to all stakeholders.

- Keep current with technical and industry developments.

Key Responsibilities :

Custom Model Development :

- Design, develop, and deploy custom machine learning models to solve complex business problems.

- Collaborate with data scientists and stakeholders to understand requirements and translate them into technical solutions.

Model Training and Evaluation :

- Implement and optimize machine learning algorithms to train models on custom datasets.

- Evaluate model performance using appropriate metrics and refine models to enhance accuracy and efficiency.

Data Preprocessing and Feature Engineering :

- Perform data preprocessing tasks such as cleaning, normalization, and transformation to prepare data for model training.

- Develop and implement feature engineering techniques to extract meaningful features from raw data.

Algorithm Optimization :

- Explore and experiment with various machine learning algorithms to identify the best fit for specific use cases.

- Optimize algorithms for speed, scalability, and accuracy.

Deep Learning and NLP :

- Develop and implement deep learning models for complex tasks such as image recognition, speech recognition, and natural language processing (NLP).

- Work on NLP projects including text classification, sentiment analysis, named entity recognition, and machine translation.

Collaboration and Documentation :

- Work closely with cross-functional teams to integrate machine learning solutions into production environments.

- Document the development process, including methodologies, code, and results for reproducibility and knowledge sharing.

Qualifications :

Experience :

- 4-5 years of hands-on experience in machine learning model development and deployment.

- Proven experience in training and fine-tuning machine learning models on custom datasets.

Technical Skills :

- Proficiency in Python and familiarity with machine learning libraries such as TensorFlow, PyTorch, Scikit-Learn, and Keras.

- Strong understanding of various machine learning algorithms (e.g, regression, classification, clustering, neural networks) and their applications.

- Experience with data preprocessing and feature engineering techniques.

- Knowledge of optimization techniques and best practices for model training.

Deep Learning and NLP Skills :

- Proficiency in developing and deploying deep learning models using frameworks like TensorFlow or PyTorch.

- Experience with NLP libraries and frameworks such as NLTK, SpaCy, Hugging Face Transformers, and BERT.

- Strong understanding of deep learning architectures (e.g, CNNs, RNNs, LSTMs) and their applications in NLP tasks.

Additional Skills :

- Familiarity with version control systems (e.g, Git) and collaborative development workflows.

- Experience with cloud platforms (e.g, AWS, GCP, Azure) for machine learning model deployment.

- Understanding of big data technologies and frameworks (e.g, Hadoop, Spark) is a plus.

Soft Skills :

- Excellent problem-solving skills and the ability to troubleshoot complex issues.

- Strong communication and collaboration skills.

- Ability to work independently and as part of a team.

- Detail-oriented with a focus on delivering high-quality results.