Work Flexibility: Hybrid

What you will do-

• Translate stakeholder requirements to potential AI & data science solutions independently.

  
  
  

• Contribute to discussions on identifying opportunities where machine learning can be applied to real-world business opportunities with key stakeholders.

  
  
  

• Support data science and AI collaboration efforts with partners across functions and teams

  
  
  

• Build and deliver presentations and communications that explain critical functions and findings to stakeholders with some guidance.

  
  
  

• Apply fundamental and some advanced concepts, practices and procedures for problem solving

  
  
  

• Automate repetitive data prep, feature engineering, and model monitoring pipelines with AI-driven tools.

  
  
  

• Explore and integrate large language models (LLMs) and generative AI solutions to accelerate exploratory data analysis, reporting, and knowledge discovery.

  
  
  

• Partner with engineering teams to operationalize models, embedding automation into core products and processes.

  
  
  

• Continuously evaluate and improve model performance using automated monitoring, retraining, and alerting systems

  
  
  

• Ability to manage individual tasks with minimal guidance and flag project risks as they are identified.

  
  
  

What you will need-

Required-

• Bachelor's Degree in data science, computer science, mathematics, statistics, or related field with applicable data science work experience. And Master's Degree or PhD in Data Science or quantitative discipline preferred.

  
  
  

• Experience- 7 years - 10 years

  
  
  

• Expert proficiency in at least one programming language central to AI and Data Science (e.g. Python).

  
  
  

• Familiarity with AI automation platforms and cloud-based native tools such as data storage, distributed computing, business intelligence, and infrastructure as code (Power BI, Azure, Fabric etc.).

  
  
  

Preferred-

• Proficient in at least two statistical techniques (e.g. time series modelling, classification, computer vision); in identifying the most appropriate statistical tool for a particular use case and project.

  
  
  

• Familiarity with a variety of visualizations (e.g. correlation heat maps, bubble charts) and demonstrate financial acumen to develop financial impacts for existing projects and evaluating new opportunities

  
  
  

• Nice to have: Microsoft Azure or Fabric data science/ AI related certifications here.