Lead Applied AI ML - Data Scientist
Role details
Job location
Tech stack
Job description
- Lead a local applied machine learning team and collaborate across a global organization to deliver high-impact outcomes.
- Define technical vision, shape strategic roadmaps, and align stakeholders across product, business, and technology.
- Translate business requirements into machine learning specifications, milestones, and agile delivery plans.
- Design experiments, implement algorithms, validate results, and productionize scalable, trustworthy, and explainable solutions.
- Refine model capabilities using PyTorch and scikit-learn; apply causal inference with DoWhy to quantify treatment effects and inform experimental decisions.
- Utilize Hugging Face Transformers and LangChain to explore counterfactual reasoning in large language models; produce research materials, internal notes, and demos that enable stakeholder adoption.
- Build and operate model development and operations workflows for training, deployment, monitoring, and continuous improvement.
- Exercise sound technical judgment, anticipate bottlenecks, and balance business needs with technical constraints.
- Mentor and coach team members, foster an inclusive culture, and grow talent.
- Contribute to firmwide machine learning communities through publications, talks, patents, and knowledge sharing.
- Evaluate and improve processes that enhance execution, communication, and accountability.
Requirements
As Lead Applied AI ML - Data Scientist within the Commercial & Investment Bank's team, you'll leverage your technical expertise and leadership abilities to support AI innovation. You should have deep knowledge of AI/ML and effective leadership to inspire the team, align cross-functional stakeholders, engage senior leadership, and drive business results., * Masters with 7+ years experience or PhD with 3+ years of experience in Computer Science, Information Systems, Statistics, Mathematics, or equivalent experience.
- Track record of managing AI/ML or software development teams.
- Experience as a hands-on practitioner developing production AI/ML solutions.
- Knowledge and experience in machine learning and artificial intelligence. Ability to set teams up for success in speed and quality, and design effective metrics and hypotheses.
- Expert in at least one of the following areas: Large Language Models, Natural Language Processing, Knowledge Graph, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.
- Good understanding of Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics.
- Must have good knowledge on agentic patterns and relevant frameworks, such as LangChain, LangGraph, Auto-GPT etc.
- Strong understanding of AI implementation in software development and legacy code transformation.
- Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, AI evaluation, RAG (Similarity Search).
- Demonstrated expertise in machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn.
- Programming knowledge of python, spark; Strong grasp on vector operations using numpy, scipy etc
Preferred qualifications, capabilities and skills
- Familiarity in AWS Cloud services such as EMR, Sagemaker etc.,
- Strong people management and team-building skills. Ability to coach and grow talent, foster a healthy engineering culture, and attract/retain talent. Ability to build a diverse, inclusive, and high-performing team.
- Ability to inspire collaboration among teams composed of both technical and non-technical members. Effective communication, solid negotiation skills, and strong leadership.
Benefits & conditions
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
