Data Scientist

Role & responsibilities

Description:

Data Scientist
Job Summary:
We are looking for a results-oriented Data Scientist with expertise in Statistics, Economics, Machine Learning, Deep Learning, Computer Vision, and Generative AI. The ideal candidate will have a proven track record of building and deploying predictive models, conducting statistical analysis, and applying cutting-edge AI techniques to solve real-world business challenges.
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Key Responsibilities:

Good to Have Palantir Foundry Experience:

Experience using Foundry Code Workbooks for developing and deploying machine learning models.
Leveraging Foundry Ontology to access and interpret structured enterprise data for modeling.
Familiarity with Foundry's AI/ML integration capabilities, including support for Python, Spark, and external ML libraries.
Building interactive dashboards and analytical apps using Foundry's visualization tools.
Collaborating within Foundry's shared workspace for reproducible and auditable data science workflows.
Experience deploying models and integrating them into Foundry Operational Workflows for real-time decision support.

• Develop models for regression, classification, clustering, and time series forecasting.
• Perform hypothesis testing and statistical validation to support data-driven decisions.
• Build and optimize deep learning models (ANN, CNN, RNN including LSTM, BERT).
• Implement computer vision solutions using YOLOv3, SSD, U-Net, R-CNN, etc.
• Apply Generative AI and LLMs (GPT-4, LLaMA2, Bard) for NLP and content generation.
• Create interactive dashboards and applications using Streamlit or Flask.
• Deploy models using AWS SageMaker, Azure, Docker, Kubernetes, and Jenkins.
• Collaborate with cross-functional teams to integrate models into production.
• Handle large datasets using SQL/NoSQL and PySpark.
• Stay updated with the latest AI/ML research and contribute to innovation.
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Technical Skills:
Programming & Frameworks:
• Languages: Python
• Libraries/Frameworks: TensorFlow, PyTorch, Keras, Flask, Transformers, Langchain, PySpark, Caffe
• Visualization & Data Tools: Pandas, NumPy, Seaborn, Matplotlib, Scikit-learn, Scipy, NLTK, Streamlit, OpenCV, Scikit-Image, Dlib, MXNet, Fasta
ML & Statistical Techniques:
• Regression (Linear/Logistic), Decision Trees, Random Forest, KNN, Nave Bayes
• Clustering (KMeans, Hierarchical), Time Series Forecasting
• Hypothesis Testing, Statistical Inference
Deep Learning & Computer Vision:
• ANN, CNN, RNN (LSTM, BERT), VGGs, YOLOv3, SSD, HOGs, DCGAN, U-Net, R-CNN, NEAT, Inpainting
Gen-AI / LLMs:
• HuggingFace, GPT-4, Bard, LLaMA2, Pinecone, Palm, GenAI Studio, OpenAI fine-tuning

Deployment & DevOps:
• AWS (SageMaker), Azure, Docker, Kubernetes, Jenkins, Git, GitHub, API integration
Databases & Tools:
• MySQL, NoSQL
• Jupyter Notebook, Google Colab, Visual Studio, Power BI
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Qualifications:
• Bachelor’s or Master’s in Statistics, Economics, Computer Science, Data Science, or related field.
• Demonstrated experience in developing and deploying models in production.
• Strong analytical and statistical skills.
• Excellent communication and collaboration abilities

Preferred candidate profile