Candidates with agentic AI experience and advanced statistical modeling skills will find this role in Bangalore emphasizing cross-functional collaboration and scalable data science solutions.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Brillio 2 via Lever
Senior Data Scientist
Job requirements:
Experience Range: 5 - 8 years of experience, including at least 5 years of hands-on work in data science, analytics, or related fields, with recent exposure to agentic AI solutions Key Responsibilities:
- Translate complex business challenges into structured data science problems, ensuring alignment with organizational objectives and measurable outcomes
- Develop, monitor, and validate OKRs using advanced statistical techniques to deliver actionable insights and track progress
- Execute advanced data wrangling, cleansing, and transformation on large, complex datasets to enable robust modeling and analysis
- Deliver impactful data-driven insights through clear data storytelling, utilizing visualization tools to communicate findings effectively to stakeholders
- Apply design thinking methodologies to create innovative analytical solutions and continuously optimize data science workflows and processes
- Lead technical decision-making for modeling iterations, optimizing model performance, and balancing computational efficiency with business requirements
- Collaborate with cross-functional teams, including engineering and product, to implement scalable data science solutions that drive business value
- Promote data literacy and foster a culture of data-driven decision-making by sharing best practices and industry trends across the organization
Required Skills:
- Advanced proficiency in Python or R for data wrangling, preprocessing, and statistical analysis
- Expertise in statistical modeling and validation of performance metrics
- Experience with data visualization tools such as Tableau, Power BI, or Matplotlib
- Hands-on experience with machine learning algorithms and evaluation metrics
- Strong background in feature engineering and data mining
- Familiarity with big data technologies such as Spark or Hadoop
- Experience with cloud-based data platforms including AWS, Azure, or Google Cloud
- Knowledge of MLOps practices and deployment pipelines
Preferred Skills:
- Experience with deep learning frameworks such as TensorFlow or PyTorch
- Exposure to agentic AI and rapid domain adaptation
- Experience with automation tools and scripting for data workflows
Desired Qualifications:
- Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline
- Certification in Data Science or Machine Learning from a recognized institution, such as Microsoft Certified: Azure Data Scientist Associate or IBM Data Science Professional Certificate
- Relevant coursework or certification in statistical analysis or business analytics
Source: Brillio 2 careers (Lever)