Data Scientist
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Job Location:
Monthly Salary:
Posted on:
16-10-2025
Vacancies:
1 Vacancy
Job Summary
Job Summary (List Format) for Data Scientist Role:
- Develop and deploy predictive models for regression classification clustering and time series forecasting.
- Perform hypothesis testing and statistical validation to support data-driven decision making.
- Design and optimize deep learning models (including ANN CNN RNN LSTM BERT).
- Implement computer vision solutions using state-of-the-art architectures (YOLOv3 SSD U-Net R-CNN).
- Apply Generative AI and Large Language Models (LLMs) such as GPT-4 LLaMA2 and Bard for NLP and content generation.
- Create interactive dashboards and web applications using Streamlit or Flask.
- Deploy models into production environments using AWS SageMaker Azure Docker Kubernetes and Jenkins.
- Collaborate with cross-functional teams to integrate AI/ML solutions into business processes.
- Work with large datasets using SQL/NoSQL databases and PySpark for data handling and processing.
- Stay updated on the latest advancements in AI/ML and contribute to ongoing innovation.
Technical Skills Required:
- Strong programming skills in Python and experience with libraries like TensorFlow PyTorch Keras Flask Transformers Langchain PySpark and Caffe.
- Proficient in data analysis and visualization tools (Pandas NumPy Seaborn Matplotlib Scikit-learn Scipy NLTK Streamlit OpenCV Scikit-Image Dlib MXNet Fasta).
- Experience with machine learning techniques (regression decision trees random forest KNN Na ve Bayes clustering time series forecasting hypothesis testing).
- Knowledge of deep learning and computer vision frameworks (VGGs YOLOv3 SSD HOGs DCGAN U-Net R-CNN NEAT Inpainting).
- Familiarity with Generative AI and LLMs (HuggingFace GPT-4 Bard LLaMA2 Pinecone Palm GenAI Studio OpenAI fine-tuning).
- Skilled in deployment and DevOps tools (AWS SageMaker Azure Docker Kubernetes Jenkins Git GitHub API integration).
- Experience with databases (MySQL NoSQL) and tools like Jupyter Notebook Google Colab Visual Studio Power BI.
Qualifications:
- Bachelors or Masters degree in Statistics Economics Computer Science Data Science or related field.
- Proven experience in developing and deploying AI/ML models in production environments.
- Strong analytical statistical communication and collaboration skills.
- Develop and deploy predictive models for regression classification clustering and time series forecasting.
- Perform hypothesis testing and statistical validation to support data-driven decision making.
- Design and optimize deep learning models (including ANN CNN RNN LSTM BERT).
- Implement computer vision solutions using state-of-the-art architectures (YOLOv3 SSD U-Net R-CNN).
- Apply Generative AI and Large Language Models (LLMs) such as GPT-4 LLaMA2 and Bard for NLP and content generation.
- Create interactive dashboards and web applications using Streamlit or Flask.
- Deploy models into production environments using AWS SageMaker Azure Docker Kubernetes and Jenkins.
- Collaborate with cross-functional teams to integrate AI/ML solutions into business processes.
- Work with large datasets using SQL/NoSQL databases and PySpark for data handling and processing.
- Stay updated on the latest advancements in AI/ML and contribute to ongoing innovation.
Technical Skills Required:
- Strong programming skills in Python and experience with libraries like TensorFlow PyTorch Keras Flask Transformers Langchain PySpark and Caffe.
- Proficient in data analysis and visualization tools (Pandas NumPy Seaborn Matplotlib Scikit-learn Scipy NLTK Streamlit OpenCV Scikit-Image Dlib MXNet Fasta).
- Experience with machine learning techniques (regression decision trees random forest KNN Na ve Bayes clustering time series forecasting hypothesis testing).
- Knowledge of deep learning and computer vision frameworks (VGGs YOLOv3 SSD HOGs DCGAN U-Net R-CNN NEAT Inpainting).
- Familiarity with Generative AI and LLMs (HuggingFace GPT-4 Bard LLaMA2 Pinecone Palm GenAI Studio OpenAI fine-tuning).
- Skilled in deployment and DevOps tools (AWS SageMaker Azure Docker Kubernetes Jenkins Git GitHub API integration).
- Experience with databases (MySQL NoSQL) and tools like Jupyter Notebook Google Colab Visual Studio Power BI.
Qualifications:
- Bachelors or Masters degree in Statistics Economics Computer Science Data Science or related field.
- Proven experience in developing and deploying AI/ML models in production environments.
- Strong analytical statistical communication and collaboration skills.
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
