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Director of Applied AI and Data Science COE+RD

SALARY: Open

LOCATION: Chicago, IL/Houston, TX/Salt Lake City, UT

3 days in office and 2 days remote

We need a person from a big 4 firm. 10 years AI data science experience developing and deploying AI driven solutions and models. This is particularly within legal or consulting services. advanced degrees and certifications this is to develop AI & Data science strong management strong soft skills and presence

As the Director of Applied AI and Data Science, you will orchestrate a new era of innovation and impact at the crossroads of technology and law. Your leadership will not only drive advancements in AI but also help shape the future of legal services to maximize impact for our clients. This position offers the rare opportunity to blend technical prowess with strategic foresight, making a tangible difference in our firm and the industry at large.

Essential Functions:

• Lead and expand the strategic vision for deploying AI and advanced analytics within our firm, translating cutting-edge technology into practical, impactful legal solutions.
• Champion the identification, assessment, and prioritization of AI/advanced analytics use cases to revolutionize both our legal practices and business operations.
• Cultivate a high-calibre, cross-functional team of data scientists and responsible AI specialists, fostering a culture of excellence, innovation, and ethical AI.
• Drive collaboration across a diverse set of stakeholders through a unique hub and spoke model, ensuring the alignment of technology initiatives with business objectives.
• Oversee the development and implementation of proof-of-concepts and AI model deployment, ensuring seamless integration and value creation within our legal framework.
• Be the vanguard for a culture of continuous learning and knowledge exchange within the AI and Data Science Center of Excellence (COE), promoting cross-team collaboration and innovation.
• Offer strategic insights and leadership on the long-term implications, risks, and ethical considerations of AI and advanced analytics in the legal sector.

Qualifications & Requirements

• Bachelor's degree in a relevant field is required, and an advanced degree or relevant certifications are highly preferred.
• Minimum of 10 years of relevant experience in AI, data science, or related fields, with a proven track record in professional services industries.
• Exceptional leadership skills, with experience in building, mentoring, and guiding high-performing, diverse teams of data scientists and AI professionals.
• Demonstrated success in developing and deploying AI-driven solutions and models, particularly within the legal or professional services sectors.
• Profound understanding of AI and advanced analytics technologies, coupled with the ability to discern their feasibility and long-term impact within the legal context.
• Exemplary communication and stakeholder management skills, adept at engaging with leadership and key stakeholders to drive consensus and action.
• A pioneering spirit, driven by a passion to enact change and deliver results in the legal field, balanced with a deep understanding of the associated long-term risks and ethical considerations.

• AI/ML Frameworks and Tools:
  • Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras.
  • Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment.
• Data Analytics and Big Data Technologies:
  • Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets.
  • Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data.
• Programming Languages:
  • Strong proficiency in programming languages such as Python, R, and SQL, crucial for data manipulation and algorithm development.
  • Familiarity with Java or Scala can be advantageous for integration with enterprise systems.
• Cloud Computing Platforms:
  • In-depth knowledge of cloud computing environments such as AWS, Azure, or Google Cloud Platform, particularly their AI and data analytics services.
• Database Management:
  • Experience with database management and querying tools, including traditional SQL databases (eg, MySQL, PostgreSQL) and NoSQL databases (eg, MongoDB, Cassandra).
• DevOps and MLOps:
  • Familiarity with DevOps practices and tools (eg, Jenkins, Docker, Kubernetes) for efficient deployment of AI solutions.
  • Understanding of MLOps principles to streamline the machine learning life cycle from experimentation to production.
• Legal-Tech Software:
  • Exposure to legal-tech software and platforms is beneficial, as it provides contextual understanding crucial for application in the legal domain.
• Security and Compliance Tools:
  • Knowledge of security protocols and compliance standards relevant to data privacy and AI ethics, especially in the legal sector.
• Collaboration and Project Management Tools:
  • Proficiency in using project management and collaboration tools (eg, JIRA, Asana, Trello) to manage AI/ML projects efficiently.
• Emerging Technologies:
  • Keen interest and understanding of emerging technologies in AI, such as natural language processing, computer vision, and predictive analytics, to stay ahead in the field.