CLOUDSUFI - Data Scientist

CLOUDSUFI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified candidates receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, and national origin status. We provide equal opportunities in employment, advancement, and all other areas of our workplace. Please explore more at https://www.cloudsufi.com/

What are we looking for:

We are seeking an experienced and innovative Senior Data Scientist to join our team. As a Senior Data Scientist with expertise in statistical analysis, machine learning, and data visualization. Proficiency in data science, NLP, computer vision, and/or machine learning projects/products in industry. Strong communication skills, business acumen, and the ability to mentor junior team members are highly valued.

Job Responsibilities:

- Design, develop, and deploy robust machine learning models using cloud platforms like GCP , AWS, Azure.

- Implement MLops best practices across the entire ML lifecycle, including data versioning, model training, validation, deployment, and monitoring Integrate CI/CD pipelines for automated model building, testing, and deployment using GCP tools (e.g., Cloud Build, Cloud Functions) or equivalent tools on other platforms.

- Clean, pre-process, and transform large datasets for analysis.

- Effectively communicate complex data insights and MLOps strategies to both technical and non-technical audiences and document them clearly concisely

- Mentor and guide junior data scientists.

- Partner with stakeholders to identify business challenges and translate them into actionable data science projects with a focus on AI and Generative AI applications.

- Develop, train, and evaluate cutting-edge machine learning models, including Generative Adversarial Networks (GANs) and transformers, for tasks like image/text generation, data augmentation, and creative content development.

- Lead and mentor junior data scientists, fostering a culture of continuous learning and innovation.

- Should have working experience on LLMs including prompt engineering, fine-tuning, Retrieval Augmented Generation (RAG), and explainability.

- Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts.

- Implement security measures to protect sensitive data.

- Collaborate with cross-functional teams to understand business challenges and objectives, translating complex data into actionable insights.

- Experience in Python, Java, R, PyMuPDF, Camelot, SpaCy, NLTK, TextBlob, PyTorch, email parser, pdf parser, Scikit-learn, XGBoost, LightGBM, Keras, reinforcement learning, Tesseract, Pytesseract.

- Experience in PostgreSQL, MySQL, Bigquery, Docker, Girt, MLflow,Linux and shell scripting

- In-depth understanding of CI/CD principles and tools for machine learning (e.g., Git, Jenkins Solid knowledge of MLOps practices and methodologies (e.g., Version Control, Model Monitoring, Experiment Tracking).

- Familiarity with Vertex AI, Vertex Pipelines, Vertex Feature Store, and Integrating with Vector Databases

- Experienced in Information Retrieval (Content Recommendation, Search Metrics, search query, document classification, entity recognition, topic modeling, etc).

Qualifications / Required Experience:

- Education : Bachelor Degree / Master's degree in Data Science .

Experience :

- 8 to 9 years of professional experience as Data Scientist.

- Minimum 6-7 years of experience with hands-on data science, NLP, computer vision, and/or machine learning projects/products in industry.

Skills :

- Deep knowledge of model development.

- Demonstrated experience applying data science methods to real-world data problems.

- Decent understanding of downstream business and supply chain.

- Must have excellent communication and interpersonal skills and work effectively in cross-functional teams.

- Able to bring ideas from conceptualization to productionalization (putting models in production) using the right tools (e.g. mlflow, kubeflow, tensorlight, etc).

- Experience utilizing visualization tools to take advantage of the growing volume of available information.

- Experience in Oil & Gas, Finance and Logistics is a plus.