Responsibilities
- Assist our customers in identifying, evaluating, and prioritizing AI-ready use cases.
- Design, develop, and implement complex machine learning models and algorithms to solve real-world business problems.
- Collaborate with cross-functional teams, including data engineers, analysts, and subject matter experts, to understand business requirements and translate them into data science solutions.
- Lead client-facing project teams of AHEAD data science and AI experts.
- Develop and train custom models using frameworks such as Scikit-Learn, TensorFlow or PyTorch.
- Leverage Jupyter-based environments for exploratory data analysis, model development, and deployment.
- Communicate complex technical concepts and findings to stakeholders and leadership in a clear and concise manner.
- Mentor and provide guidance to junior data scientists.
- Participate in pre-sales activities, including project scoping, estimation, and solution design.
- Educate clients and stakeholders on data science and machine learning concepts, methodologies, and best practices.
- Contribute to the development and enhancement of AHEAD's data science service offerings and thought leadership.
Qualifications
- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
- Minimum of 7 years of experience with 5 years of experience in a data science-related role, with a focus on machine learning and deep learning.
- Proficient in Python, with experience in libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, and Matplotlib.
- Experience with developing and training custom models using TensorFlow, PyTorch, or scikit-learn.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Hands-on experience with Jupyter Notebooks, Azure Machine Learning Studio, Azure OpenAI, AWS SageMaker, and AWS Bedrock.
- Strong understanding of machine learning algorithms, including supervised and unsupervised learning techniques.
- Experience with key generative AI concepts including fine-tuning and retrieval-augmented generation.
- Strong understanding of the machine learning lifecycle, including model deployment, monitoring, drift detection/retraining, and canary testing
- Excellent analytical and problem-solving skills with the ability to work on complex data science challenges.
- Strong communication and collaboration skills, with the ability to present complex technical information to both technical and non-technical audiences.
- Experience in pre-sales activities, including project scoping, estimation, and solution design.
Nice to Have
- Experience training and deploying models on DataRobot or Dataiku platforms.
- Domain expertise in specific industries or areas of application (e.g., finance, healthcare, e-commerce).
- Familiarity with data platform architectures, database design, and BI platform such as PowerBI.
- Knowledge of identifying and applying non-predictive or generative methods to business problems, including ad-hoc analysis, linear programming (optimization), or designing and running simulations.
- Wide knowledge of the current state of ML and AI technology and market.
- Experience writing AI and ML blogs and go to market materials.
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