What are the responsibilities and job description for the Communications Advanced Analytics & AI Solutions - Vice President position at JPMorgan Chase?
Join us to shape the future of communications analytics at JPMorgan Chase. As a Data Scientist in the Communications Data Solutions team, you will play a pivotal role in developing and deploying innovative AI and advanced analytics solutions that empower decision-making and deliver actionable insights. You will collaborate with technology teams, business stakeholders, and external partners to design scalable models and analytical frameworks that support communications teams firmwide.
As a Data Scientist in Communications Data Solutions, you will Lead the development and deployment of advanced analytics and AI solutions to analyze communications data from diverse internal and external sources. Design, build, and implement predictive models, statistical analyses, and machine learning algorithms to uncover insights and drive business strategy. Collaborate with data engineers, technology teams, and external agencies to ensure seamless integration of data science solutions into centralized databases and BI platforms. Partner with communications teams across the firm to understand their business needs and deliver tailored analytical solutions. Develop and maintain robust evaluation frameworks to monitor model performance, ensuring continuous improvement and alignment with business objectives. Identify opportunities for process automation and AI-driven innovation, enhancing operational efficiency and impact. Document analytical methodologies, model metadata, and AI processes for transparency, compliance, and knowledge sharing.Foster a culture of excellence, innovation, and continuous learning within the data science community.
Job Responsibilities:
- Design and implement advanced analytics and machine learning models for communications data analysis.
- Apply statistical analysis, predictive modeling, and AI/ML techniques to extract insights from large, complex datasets.
- Collaborate with data engineers to optimize data pipelines and ensure high-quality data for modeling and analysis.
- Partner with communications teams and external agencies to understand analytical requirements and deliver impactful solutions.
- Develop and manage BI dashboards and visualizations to communicate findings and support decision-making.
- Identify and implement process improvements, automating manual workflows where possible.
- Document analytical processes, model assumptions, and results for transparency and compliance.
Required qualifications, capabilities, and skills:
- Advanced degree in Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence, or a related quantitative field.
- Proven experience in data science, machine learning, and advanced analytics, with a track record of deploying models in production at scale.
- Strong proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, Pandas, NumPy).
- Experience with LLM and other related frameworks like Langchain, LLamaIndex, AutoGen, ReAct , GPT and Claude models,
- Hands-on expertise in BI platforms and tools (e.g., Tableau, ThoughtSpot) for advanced analytics and data visualization.
- Experience with cloud platforms (Databricks, AWS, Azure) and deploying/managing machine learning models in production environments.
- Deep understanding of statistical analysis, experimental design, and model evaluation techniques.
- Demonstrated ability to collect, refine, and analyze data from diverse sources, including third-party tools and external agencies.
- Excellent analytical, problem-solving, and communication skills, with the ability to convey complex technical concepts to diverse audiences.
- Experience working with cross-functional teams in a dynamic, fast-paced environment.
- Experience partnering with business stakeholders to deliver data-driven solutions that drive measurable impact.