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Data Scientist II
Junglee GamesData Scientist at Junglee Games developing deep learning and NLP solutions. Building scalable models and conducting experimentation for real-world gaming business problems.
Tech Stack
Tools & technologiesPythonPyTorchSQLTensorflow
About the role
Key responsibilities & impact- Design, develop, and optimise deep learning models for real-world business problems
- Build and fine-tune NLP models using transformers (BERT family models, Llama, GPT, T5, etc.)
- Work on tasks such as text classification, information extraction, semantic search, summarization and recommendation
- Conduct model experimentation, evaluation, and hyperparameter tuning
Requirements
What you’ll need- 3–5 years of hands-on experience as a Data Scientist
- Strong Python and SQL
- Hands-on experience with PyTorch and/or TensorFlow
- Solid understanding of: Neural networks, RNNs, LSTMs, Attention mechanisms
- Transformer architectures and pre-trained language models.
- Strong background in NLP techniques and Embedding methods.
- Experience with data preprocessing, feature engineering, and model evaluation
- Comfortable working with large unstructured datasets
Benefits
Comp & perks- Value Customers & Data - Prioritize customers, use data-driven decisions, master KPIs, and leverage ideation and A/B testing to drive impactful outcomes.
- Inspire Extreme Ownership - We embrace ownership, collaborate effectively, and take pride in every detail to ensure every game becomes a smashing success.
- Lead with Love - We reject micromanagement and fear, fostering open dialogue, mutual growth, and a fearless yet responsible work ethic.
- Embrace change - Change drives progress, and our strength lies in adapting swiftly and recognizing when to evolve to stay ahead.
- Play the Big Game - We think big, challenge norms, and innovate boldly, driving impactful results through fresh ideas and inventive problem-solving.
ATS Keywords
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Hard Skills & Tools
PythonSQLPyTorchTensorFlowNeural networksRNNsLSTMsAttention mechanismsNLP techniquesEmbedding methods