Job Title- Lead Data Scientist-Lead Engineer, VP

Location- Pune, India

Role Description:

• The Deutsche India is seeking a talented and driven Lead Data Scientist to join our growing team. At the “Service Solutions and AI” Domain, our mission is to revolutionize our Private Bank process landscape by implementing holistic, front-to-back process automation. And being a Private Bank AI Centre of Excellence we are responsible for strategy building and execution of AI innovation, governance, and delivery across Private Bank, ensuring standardization, compliance, and accelerated adoption of AI solutions. We are dedicated to leveraging the power of data to drive innovation, optimize operations, and deliver exceptional value to our customers. We are committed to enhancing efficiency, agility, and innovation, with a keen focus on aligning every step of our process with the customer’s needs and expectations. Our dedication extends to driving innovative technologies, such as AI & workflow services, to foster continuous improvement. We aim to deliver “best in class” solutions across products, channels, brands, and regions, thereby transforming the way we serve our customers and setting new benchmarks in the industry.
• As a Lead Data Scientist, you will be responsible for the full lifecycle of data science projects, from problem definition and data acquisition to model deployment and performance monitoring. You will work closely with cross-functional teams, including product managers, engineers, and business stakeholders, to identify opportunities for data-driven solutions and translate business needs into technical requirements. We are looking for someone passionate about uncovering hidden patterns in data and communicating their findings effectively to both technical and non-technical audiences.

What we’ll offer you:

As part of our flexible scheme, here are just some of the benefits that you’ll enjoy

• Best in class leave policy
• Gender neutral parental leaves
• 100% reimbursement under childcare assistance benefit (gender neutral)
• Sponsorship for Industry relevant certifications and education
• Employee Assistance Program for you and your family members
• Comprehensive Hospitalization Insurance for you and your dependents
• Accident and Term life Insurance
• Complementary Health screening for 35 yrs. and above

Your key responsibilities

• Strategic Problem Framing & Business Translation:
  • Business Problem Definition: Lead the definition and framing of complex business problems into clear, actionable data science questions, and strategically identify the most relevant data sources to address them.
• Advanced Data Management & Preparation:
  • Data Acquisition & Wrangling: Oversee and execute the collection, cleaning, and preprocessing of large and complex datasets from various internal and external sources, ensuring data quality and readiness for analysis.
• Cutting-Edge Algorithm & Model Development:
  • Algorithm Research & Implementation: Drive research and implementation of suitable Machine Learning (ML) algorithms and tools, staying at the forefront of the latest ML research to select and customize the most effective algorithms for specific business challenges.
  • Exploratory Data Analysis (EDA): Lead in-depth exploratory data analysis to uncover data characteristics, identify critical trends, and formulate robust hypotheses.
  • Model Development & Evaluation: Architect, develop, implement, and rigorously evaluate advanced machine learning models (e.g., supervised, unsupervised, reinforcement learning) to solve complex business problems, ensuring high performance, scalability, and interpretability.
• Experimentation & Impact Measurement:
  • Experiment Design & Hypothesis Testing: Design and execute sophisticated experiments to test hypotheses and precisely measure the tangible impact of data-driven solutions on business outcomes.
• Effective Communication & MLOps Leadership:
  • Reporting & Strategic Presentation: Communicate complex analytical findings and strategic recommendations clearly and concisely to diverse audiences, including senior leadership and non-technical stakeholders, through compelling reports, interactive dashboards, and engaging presentations.
  • MLOps & Productionization Leadership: Collaborate effectively with engineering teams to lead the deployment, maintenance, and monitoring of data science models in production environments, championing MLOps best practices for operational excellence.
• Continuous Innovation & Collaborative Leadership:
  • Continuous Learning & Innovation: Continuously research and explore new data science techniques, tools, and technologies to enhance organizational capabilities, foster innovation, and maintain a competitive edge.
  • Knowledge Sharing & Community Engagement: Actively contribute to the data science community within the company by sharing advanced knowledge, best practices, and innovative approaches, mentoring junior team members.
  • Agile Participation & Leadership: Actively lead and contribute to all Agile ceremonies, including sprint planning, daily stand-ups, retrospectives, and refinements, driving efficiency, accountability, and continuous improvement within the squad.
  • Cross-functional Collaboration: Foster profound collaboration with cross-functional teams, including developers, analysts, product owners, and deployment managers, to consistently achieve and exceed sprint and release objectives.
  • Product Advocacy: Serve as a vocal advocate for data science products and solutions across the organization, continuously refining and pioneering product and process best practices within the squad and beyond.

Your skills and experience

• Educational Foundation:
  • Academic Background: Graduate’s, Master’s or PhD in a quantitative field such as Computer Science, Statistics, Mathematics, Engineering, or a related discipline.
• Extensive Professional Expertise:
  • Data Science Leadership: Proven experience (13+ years) in a data scientist role, demonstrating successful application of advanced data science techniques to solve complex, real-world problems, with a strong track record of leading technical initiatives.
• Technical Mastery & Specialization:
  • Programming Mastery: Expert-level proficiency in programming languages commonly used in data science, particularly Python (with libraries like scikit-learn, pandas, NumPy) or R, SQL, etc.
  • Core Data Science & ML Knowledge: Solid understanding and execution knowledge of advanced statistical modeling, machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning), and experimental design.
  • Specialized AI Expertise: Strong knowledge and hands-on experience in ML, Natural Language Processing (NLP), Transformers, MLOps, Large Language Models (LLM), Retrieval Augmented Generation (RAG), Vector Databases, and LangChain.
  • Database Querying Skills: Expert experience with SQL for efficient data extraction and manipulation from complex databases.
  • Data Visualization Skills: Advanced familiarity with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn) to effectively communicate complex insights.
  • Cloud Platform Expertise: Strong familiarity with major cloud platforms (e.g., AWS, Azure, GCP) and their data science services, including practical deployment experience.
  • Big Data Experience (Nice to have): Experience with big data technologies (e.g., Spark, Hadoop) is a significant advantage.
  • Deep Learning Experience (Plus): Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) is a significant plus.
• Leadership & Strategic Competencies:
  • Strategic Leadership & Influence: Exceptional leadership, communication, and collaboration skills, with the ability to mentor junior engineers, influence cross-functional teams, and articulate complex technical concepts to both technical and non-technical stakeholders effectively.
  • Analytical & Problem-Solving Prowess: Superior analytical and critical problem-solving abilities, capable of navigating complex technical challenges and providing strategic, data-driven solutions.
  • Work Ethic & Adaptability: High work ethic and adaptability, thriving in a fast-paced environment and capable of leading teams through evolving priorities.
  • Proactive Innovation & Mentorship: A proactive, results-oriented, and team-centric mindset with an unwavering commitment to continuous improvement, innovation, and technical excellence, actively fostering growth in others.
  • Domain-Specific Expertise: Preferred experience in the Banking & Finance Domain, with a deep understanding of industry-specific data and business challenges.

How we’ll support you

• Training and development to help you excel in your career
• Coaching and support from experts in your team
• A culture of continuous learning to aid progression
• A range of flexible benefits that you can tailor to suit your needs

About us and our teams

Please visit our company website for further information:

https://www.db.com/company/company.html

We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.