Data Scientist / Gen AI

Job Title: Data Scientist – Generative AI & Agentic AI

Experience Level: 4–7 Years
Employment Type: Full-time

Role and Responsibilities:

• Lead and drive AI/ data science projects independently, owning the end-to-end process from data collection to model deployment.
• Apply Gen AI, NLP, Computer Vison, Deep Learning, advanced statistical and ML predictive modelling techniques to develop and implement scalable AI solutions, ensuring accuracy and reliability of models.
• Collaborate with business and cross-functional teams to understand their needs and implement AI driven solutions.
• Opportunity understanding/ problem formulation and suggest AI solutions to help the business for maximum impact. 
• Present complex results to non-technical stakeholders, translating data insights into actionable business strategies.
• Develop and deploy production-grade AI/ machine learning models in cloud-based and on-prem platforms.
• Lead cross-functional teams in the design and execution of AI/ data science projects, ensuring alignment with business objectives.
• Stay abreast of emerging technologies and industry trends, continuously enhancing expertise in AI/ data science methodologies and tools.
• Drive innovation by exploring new approaches and techniques for solving complex business problems through data analysis and AI/ ML modelling.
• Strongly support the adoption of AI/ data science across the organization.
• Contribute to the strategic planning and direction of AI/ data science initiatives within the organisation.
• Engineering: working in a multidisciplinary squad alongside architect and data engineer

We want to hear from you if you have:

• Experience working on AWS cloud.

• Demonstrated experience in data science or statistical modelling working on end-to-end projects, preferably within retail banking or financial services.
• Advanced technical skills - ability to generate actionable value-add insights by understanding complex data and using tools such as Python, R, Spark, Teradata SQL, SAS and experience in working with Big Data Platforms, e.g. Hadoop/HDFS, Omnia and etc, using Hive and/or Spark
• Knowledge of Agentic AI, Deep Learning, Natural Language Processing (NLP), Computer Vision, Large Language Models (LLM), Generative AI (e.g., Open-source models & GTP’s, RAG, Guardrails for fairness / privacy)
• Knowledge of H2O.ai, GitHub, Big Data and ML Engineering
• A relevant tertiary qualification e.g. Mathematics, Statistics, Economics, Econometrics, Computer Science or Engineering
• Experience in a risk or audit domain would be beneficial.

About You:

• You enjoy tackling exciting and challenging business problems.
• You have an innovation mindset blended with pragmatic thinking
• You use a combination of commercial thinking and analytically driven results to formulate new ideas for the business.
• You’re driven and love to work with others to solve problems and provide the best possible solutions for your stakeholders.
• You enjoy a collaborative team environment and want to help foster a positive and inclusive culture that promotes development and growth

S​YNECHRON’S DIVERSITY & INCLUSION STATEMENT
 

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

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