Data Scientist

As an experienced Data Scientist for this remote opportunity, you will be responsible for designing and implementing end-to-end ML solutions covering structured data, text, and image modalities. You will apply rigorous statistical thinking, such as experimental design and A/B testing, to validate hypotheses. Additionally, you will be involved in developing computer vision pipelines for detection, segmentation, or recognition tasks based on business requirements. Your role will also include evaluating, selecting, and integrating foundation models and open-source checkpoints appropriately. You will be accountable for the performance of models from training to production stage, including monitoring drift, retraining, and version management. Moreover, you will have the opportunity to mentor junior data scientists and contribute to internal tooling and best practices. Key Responsibilities: - Design and ship end-to-end ML solutions for structured data, text, and image modalities - Apply statistical thinking to validate hypotheses and perform experiments - Develop computer vision pipelines for detection, segmentation, or recognition tasks - Evaluate, select, and integrate foundation models and open-source checkpoints - Own model performance from training through production - Mentor junior data scientists and contribute to internal tooling and best practices Qualifications Required: - Strong grounding in probability theory, distributions, and maximum likelihood estimation - Practical experience with gradient boosting (XGBoost, LightGBM), regularised regression, and SVMs - Ability to design statistically sound experiments with appropriate power analysis and significance testing - Familiarity with Bayesian frameworks such as PyMC, Stan, or Pyro for uncertainty quantification - Hands-on experience with fine-tuning or adapting open-source LLMs (Llama, Mistral, Falcon, or similar) - Ability to design and evaluate retrieval-augmented generation pipelines using vector databases - Proficiency in detection and segmentation frameworks, vision transformer architectures, and real-world CV challenges Note: No additional details about the company were provided in the job description. As an experienced Data Scientist for this remote opportunity, you will be responsible for designing and implementing end-to-end ML solutions covering structured data, text, and image modalities. You will apply rigorous statistical thinking, such as experimental design and A/B testing, to validate hypotheses. Additionally, you will be involved in developing computer vision pipelines for detection, segmentation, or recognition tasks based on business requirements. Your role will also include evaluating, selecting, and integrating foundation models and open-source checkpoints appropriately. You will be accountable for the performance of models from training to production stage, including monitoring drift, retraining, and version management. Moreover, you will have the opportunity to mentor junior data scientists and contribute to internal tooling and best practices. Key Responsibilities: - Design and ship end-to-end ML solutions for structured data, text, and image modalities - Apply statistical thinking to validate hypotheses and perform experiments - Develop computer vision pipelines for detection, segmentation, or recognition tasks - Evaluate, select, and integrate foundation models and open-source checkpoints - Own model performance from training through production - Mentor junior data scientists and contribute to internal tooling and best practices Qualifications Required: - Strong grounding in probability theory, distributions, and maximum likelihood estimation - Practical experience with gradient boosting (XGBoost, LightGBM), regularised regression, and SVMs - Ability to design statistically sound experiments with appropriate power analysis and significance testing - Familiarity with Bayesian frameworks such as PyMC, Stan, or Pyro for uncertainty quantification - Hands-on experience with fine-tuning or adapting open-source LLMs (Llama, Mistral, Falcon, or similar) - Ability to design and evaluate retrieval-augmented generation pipelines using vector databases - Proficiency in detection and segmentation frameworks, vision transformer architectures, and real-world CV challenges Note: No additional details about the company were provided in the job description.