Senior Data Scientist

JOB SUMMARY

You will be mainly working as a data scientist with additional roles and responsibilities as a lead data scientist in one of the following domains: NLP/GenAI/Voice, Graph Analytics, Geospatial AI, Capability building. You will work with a group of data scientists in a Research and Development group. The roles and task assignments in the team are dynamic, you along with other data scientists will work on multiple strategic projects with cutting edge innovation potential to create POCs of innovative ideas starting from ideation to development and implementation.

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Collaborate closely with business stakeholders to understand their processes, business problems, challenges, and objectives. Identify opportunities to leverage AI and the respective domain expertise to drive efficiency, improve decision-making, and enhance customer experience.
• Goal alignment: Aligns stakeholder interests with the domain team's strategic objectives.
• Collaborate with a cross-functional team of data scientists, engineers, and subject matter experts to create and develop innovative AI solutions.
• Establishes a wide network of contacts across the organization to solicit information. Proactively reaches out and gathers key information.
• Experimentation and prototyping:
  Lead and strong individual contributor driving technology development for our AI research experimentation and innovative prototype development
  . Brings new emerging AI tech into relevant prototypes for the company. Facilitates the data science lifecycle from data collection to model deployment in collaboration with relevant stakeholders and partners.
• Identify, collect, and curate relevant data from diverse sources, including open-source, government, and internal infrastructure. Ensure data quality, privacy, and security compliance.
• Manage and oversee AI projects within your domain, ensuring timely delivery, adherence to quality standards, and alignment with business objectives.
• Creates and maintains roadmaps of the team to provide a high-level framework for strategy, timing and future work.
• Fosters a culture of innovation and knowledge sharing within the AI team. Shares insights, best practices, and technical concepts effectively to both technical and non-technical audiences.
• Ensures the success of the domain through management of the related projects along with appropriate stakeholder management.
• Stays up to date on the latest advancements in AI research and development; and communicates findings and technical concepts effectively to both technical and non-technical audiences.
• Serves as a subject matter expert in AI, providing guidance, consultation, and collaboration across the bank.
• Connects and collaborates with academic partners
• Publication contributor: Leads or co-authors at least 1 relevant publication per year that is peer-reviewed at recognized conferences/journals in the field
• Drives initiatives to promote the adoption of AI across the bank, providing guidance, training, and support to various departments.

KEY PERFORMANCE INDICATOR

• Project and domain performances
• Prototype building, fail fast experiments, deployment of new strategic initiatives that passed POC
• Academic and Innovation Interactions [Submission of grants and awards, Scientific Paper Publication]
• Improvement to teams Ways of Working
• Learning sessions conducted
• Adoption of AI for enterprise use.

EDUCATIONAL ATTAINMENT

• Preferably a Master's degree in a field related to AI and Data Science, such as Computer Science, Statistics, Data Engineering, Applied Mathematics, etc.

TOOLS NEEDED

• Proficiency in Python to do data science tasks. Preferably experienced in using Jupyter notebooks.
• Familiarity with at least one data science development platform, such as Databricks, Cloudera or any similar platform.
• Familiarity with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.
• Basic understanding of JavaScript for debugging and interacting with web-based applications.
• Ability to manage and provision cloud services on platforms like AWS, Azure, or GCP for cloud compute and data products.
• Proficiency in SQL for working with relational databases.
• Experience with interacting with NoSQL databases.
• Data visualization tools such as Matplotlib, Seaborn or Plotly
• Basic familiarity with analytics tools used for dashboarding such as PowerBI or Tableau.
• Proficiency in version control systems for collaboration like Git.
• Ability to create proof of concepts and minimum viable products or applications. Including setting up necessary infrastructures and application design.

SOFT SKILLS NEEDED

• Effectively communicate and collaborate with stakeholders to understand their needs, align expectations, and drive project success. Can communicate complex AI insights to non-technical teams.
• Possess a deep understanding of fundamental AI concepts, including machine learning, deep learning, and neural networks.
• Conduct A/B testing experiments to evaluate the effectiveness of AI models and optimize their performance.
• Have experience developing minimum viable product (MVP) applications to quickly iterate and gather user feedback.
• Understand basic database principles and techniques to ensure efficient data storage, retrieval, and query performance.
• Apply knowledge of system architecture and performance optimization to improve the efficiency and scalability of AI solutions.
• Proficient in creating scripts to automate repetitive tasks and streamline workflows.
• Skilled in web scraping techniques to extract data from websites for analysis and training.
• Demonstrate strong technical capabilities and a willingness to learn new technologies and tools.
• Possess excellent problem-solving and analytical skills to identify and address challenges in AI projects.
• Ability to work independently with minimal supervision while maintaining high standards of quality and productivity.
• Easily learn and integrate new features and capabilities into existing systems.
• Strong knowledge of machine learning, deep learning and statistical modeling

TRAINING AND CERTIFICATIONS

• (plus) Data Science Certifications
• (plus) AWS Cloud Certifications

EXPERIENCE

• Minimum 3+ years of experience developing AI projects in an industry setting