Data Scientist (Responsible AI), Strategy and Talent

Job ID: 19406

Location: Bangalore, IN

Area of interest: Data and Analytics

Job type: Regular Employee

Work style: Office Working

Opening date: 11 Mar 2025

• Responsible AI advocacy: You will act as the beacon of change and advocacy on human-centered AI, responsible AI, data and AI ethics, cross all cross-functional and S&T business engagements, to cross-pollinate ideas and values.
• AI-innovation measurements: You will guide teams to understand AI methods, data, and insights. You will design and advice logical desirability signals, qualitative, and quantitative metrics to evaluate the return of investment on AI and innovation solutions.
• Communication and influence: You will translate, convince, and influence S&T business and cross-functional stakeholders using clear insights, use cases, and recommendations in approachable and simple terms. You will build credibility through structure, clarity, and socialization.

• Apply technical data science expertise to support S&T AI solutions and products throughout the lifecycle of responsible AI governance and advise responsible AI adoption according to our Group RAI Standards and RAI governance process
• Bias and fairness assessment and AI explainability: Design test cases, advise methods, and deploy methods, especially on fairness, data suitability, and explainability for AIML solutions to meet internal RAI standards. You will be expected to develop, advice, consult, and/or implement testing methods to identify and mitigate biases in datasets and AI models, minimizing unjust bias.
• Create tools and processes to enhance the explainability of AI models, fostering transparency and trust in algorithm decision-making. Ensuring explainability in human factors along the AI adoption journey
• Vendor liaison: Liaise and evaluate AI offerings and technical documentations of third-party enterprise AI vendors and internal AI vendors to inform business decision making and RAI governance
• Review and validate AI use cases based on the applicable standards, assessments, and controls required to adhere to Responsible AI standards, uphold data and AI ethics, and other AI-related governance, including ongoing and future AI and data audits
• Communicate AIML methods and data concepts in simple terms to non-technical stakeholders
• Drive data and AI ethics awareness through data, insights, and/or use cases discussions with S&T stakeholders
• Embed and advocate for human-centricity in AI solutions development and downstream impact on people and processes
• Define impact metrics, measurements, and other levers of success for AI solutions and products impacting S&T business
• Partner with Responsible AI, Technology, Cybersecurity, and other cross-functional teams to inform, influence, support, and execute S&T AI solution strategy and investment decisions
• Proactively research to stay current on emerging trends, AI and data regulations, and best practices in RAI, actively proposing improvement and adaptations to our approach
• Participate in strategic initiatives and working groups that set the pace for strategic directions on (gen)AI adoption

• Display exemplary conduct and live by the Group’s Values and Code of Conduct.
• Take personal responsibility for embedding the highest standards of ethics, including regulatory and business conduct, across Standard Chartered Bank. This includes understanding and ensuring compliance with, in letter and spirit, all applicable laws, regulations, guidelines and the Group Code of Conduct.
• Effectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters.

• Embed Here for good and Group’s brand and values in team
• Perform other responsibilities assigned under Group, Country, Business or Functional policies and procedures
• Multiple functions (double hats)

• Business Communication Skills
• Critical thinking
• Data Science, Statistics
• ML, DL, NLP
• SQL, Dataiku
• Generative AI – LLMs, fine-tuning techniques
• AI ethics
• Specific skills – to craft out interview process and interview guides for interviewers later on:

• Effective business communication skills including but not limited to vendor management, data translation, and data storytelling skills
• Excellent change management and business process skills with ability to develop strategy, evaluate efficacy
• Empathetic, growth mindset, human-centric approach, entrepreneurial spirit, resourceful, excellent cross-functional, interdisciplinary collaboration skills
• Creative thinking, critical thinking, and conscientiousness

• Knowledge of AI ethics, AI risk, human-centered AI, model and data governance practices and related business and technology issues related to enterprise-wide information
• Awareness of best practices in testing bias, fairness and stability, and ability to understand results from risk management
• Experience in industry best practices of model risk management and AI fairness and explainability, including model validation, reproducibility, statistical and engineering process control, quality assurance, and data/model shift

• Real world experience with machine/deep learning, artificial intelligence, statistical analysis and modelling, natural language/computational linguistics, computer vision, signal processing, and/or generative AI, preferably in Python
• MLOps and data engineering
• Knowledge and experience with dataiku, databricks, MLOps, and both SQL and noSQL database design, queries, and storage
  

• 5+ years of work experience in a data science capacity
• OR minimum of 3+ years of work experience in a data science capacity with a Doctorate in a quantitative discipline*
• OR Field transfers from 4+ years of work experience in analytics, risks and governance, tech and operations, legal, and/or Data Privacy with a Masters, MPhil, or Ph.D. in a quantitative discipline* or 2+ equivalent data science work experience
• Real world experience with machine/deep learning, artificial intelligence, statistical analysis and modelling, natural language/computational linguistics, computer vision, signal processing, and/or generative AI, preferably in Python
• Aware of AI ethics, AI risk, human-centered AI, model and data governance practices and HR-related AI regulations and policies
• Experience influencing and partnering with cross-functional stakeholders and third-party vendors
• Effective business communication skills including but not limited to vendor management, data translation, and data storytelling skills
• Bachelor’s degree in Computer Science, Data Science, Statistics, Artificial Intelligence
• Preferred Qualifications
• Masters, MPhil, or Doctorate degree in quantitative discipline* like Computer Science, Data Science, Statistics, Artificial Intelligence, Human-computer interaction, Computational Linguistics, Behavioral Sciences
• Familiarity with legal and regulatory requirements related to AI

• Hands-on experience on AI ethics and data ethics governance
• Experience working in highly regulated industries like finance and healthcare
• Practical experience with genAI (LLMs/RAG), agentic AI, dataiku, databricks, MLOps, and both SQL and noSQL database design, queries, and storage
• 5+ years of work experience in Risk Management and Governace, Privacy, Security, Compliance, Investigations, Operations, Auditing, and/or Finances
• Awareness of best practices in testing bias, fairness and stability, and ability to understand results from risk management
• Experience in industry best practices of model risk management and AI fairness and explainability, including model validation, reproducibility, statistical and engineering process control, quality assurance, and data/model shift

• Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do
• Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well
• Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term

• Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations.
• Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum.
• Flexible working options based around home and office locations, with flexible working patterns.
• Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits
• A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning.
• Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential.