Photon
Cengage | Data Scientist | Boston
Photon, Boston, Massachusetts, us, 02298
We are seeking a skilled and innovative Data Scientist to join our dynamic team. The ideal candidate will be responsible for transforming complex datasets into actionable insights, leveraging advanced statistical techniques, machine learning models, and data visualization tools. You will collaborate closely with cross-functional teams to support data-driven decision-making and contribute to impactful business outcomes. They must possess knowledge of Python and machine learning frameworks.
Responsibilities
Analyze large and complex datasets to identify patterns, trends, and insights. Develop, test, and implement machine learning models for predictive analytics. Develop and implement generative AI models, including LLMs, text-to-image and generative AI. Partner with data engineering teams to define data requirements and ensure data pipelines are optimized for analysis. Conduct hypothesis testing, A/B testing, regression analysis, and other statistical methods to validate business assumptions. Collaborate with engineering teams to deploy machine learning models into production and ensure model performance meets business needs. Collaborate with other engineers, stakeholders, and team members to develop innovative solutions. Create compelling visualizations and dashboards using tools like Tableau, Power BI, or similar to present insights to both technical and non-technical audiences. Ability to quickly identify opportunities for model improvement. Requirements
Bachelor's or master's degree in computer science, engineering, or a related field. 5+ years of experience in developing and training AI/ML models. Experience with data querying languages like SQL, scripting languages like Python, and/or statistical/mathematical software e.g. R. Knowledge of machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn. Knowledge of state-of-the-art generative AI models such as GPT, LLaMA, Gemini, and DALL-E. Experience with cloud infrastructure and platforms - Azure/GCP/AWS. Experience with data visualization tools like Tableau, Power BI, or similar. Strong understanding of deep learning, natural language processing, and computer vision. Preferred Qualifications
Bachelor's or master's degree in computer science, data science, statistics, math, physics, or other science-related discipline with coursework in AI/ML. Experience with version control systems like Git. Familiarity with cloud-based ML model deployment (e.g., Azure ML, AWS SageMaker).
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Analyze large and complex datasets to identify patterns, trends, and insights. Develop, test, and implement machine learning models for predictive analytics. Develop and implement generative AI models, including LLMs, text-to-image and generative AI. Partner with data engineering teams to define data requirements and ensure data pipelines are optimized for analysis. Conduct hypothesis testing, A/B testing, regression analysis, and other statistical methods to validate business assumptions. Collaborate with engineering teams to deploy machine learning models into production and ensure model performance meets business needs. Collaborate with other engineers, stakeholders, and team members to develop innovative solutions. Create compelling visualizations and dashboards using tools like Tableau, Power BI, or similar to present insights to both technical and non-technical audiences. Ability to quickly identify opportunities for model improvement. Requirements
Bachelor's or master's degree in computer science, engineering, or a related field. 5+ years of experience in developing and training AI/ML models. Experience with data querying languages like SQL, scripting languages like Python, and/or statistical/mathematical software e.g. R. Knowledge of machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn. Knowledge of state-of-the-art generative AI models such as GPT, LLaMA, Gemini, and DALL-E. Experience with cloud infrastructure and platforms - Azure/GCP/AWS. Experience with data visualization tools like Tableau, Power BI, or similar. Strong understanding of deep learning, natural language processing, and computer vision. Preferred Qualifications
Bachelor's or master's degree in computer science, data science, statistics, math, physics, or other science-related discipline with coursework in AI/ML. Experience with version control systems like Git. Familiarity with cloud-based ML model deployment (e.g., Azure ML, AWS SageMaker).
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