What you will do:
- Partner with business stakeholders to understand their needs, translate them into technical requirements, and develop data-driven solutions.
- Communicate complex AI concepts to non-AI stakeholders (Data Domains, Enablers, etc.) and facilitate multi-functional collaboration.
- Establish and enforce data governance policies and procedures to ensure the ethical and responsible use of data in AI applications.
- Implement Objective Key Results to measure the performance and impact of AI and automation solutions & regularly report on the progress and success of AI initiatives to the Head of Data &AI
- Lead and manage complex data science projects from inception to deployment, ensuring successful delivery and impact on business objectives.
- Develop, implement, and optimize machine learning models and algorithms to solve real-world business problems.
- Perform data cleaning, wrangling, and transformation to ensure data quality and prepare it for analysis.
- Conduct exploratory data analysis (EDA) to uncover hidden patterns, trends, and insights within data sets.
- Develop clear and concise data visualizations to effectively communicate complex findings to both technical and non-technical audiences.
- Stay up to date on the latest advancements in data science methodologies and tools, and actively seek opportunities to incorporate them into our practices.
- Mentor and guide junior data scientists within the team, fostering a collaborative and learning environment.
The skills you bring:
- PhD in Statistics, Computer Science, Mathematics, or a related field (or) master’s / bachelor’s degree with significant work experience.
- Minimum 5 to 12+ years of experience as a Data Scientist or similar role.
- Proven track record of successfully leading and delivering data science projects with tangible business impact.
- Strong expertise in LLM, deep learning, machine learning algorithms (e.g., supervised learning, unsupervised learning, reinforcement learning) and statistical modelling.
- Proficiency in programming languages such as Python, R, and familiarity with big data processing tools (e.g., Spark, Hadoop) is a plus.
- Familiarity in developing and deploying E2E AI solutions in cloud platforms (Azure, AWS, GCP)
- Excellent communication and collaboration skills, with the ability to effectively translate complex technical concepts to a non-technical audience.
- Strong problem-solving skills and a passion for applying data science techniques to solve real-world problems.
- Ability to work independently and manage multiple projects simultaneously while meeting deadlines.