About the Company/Team Our company is a leader in leveraging data-driven insights to drive business growth and innovation. Our CSS team is a dynamic and collaborative group of experts who are passionate about using cutting-edge technologies to solve complex business challenges. We value creativity, innovation, and teamwork, and we're committed to providing a supportive and inclusive environment that allows our team members to thrive. Job Summary We are seeking an experienced Senior Data Scientist to join our CSS team. As a Senior Data Scientist, you will play a key role in driving business growth by leveraging machine learning, graph modeling, and statistical techniques to solve complex business challenges. You will work cross-functionally with business and partner teams to derive actionable insights and build scalable models using massive datasets. Key Responsibilities Demonstrate deep technical expertise in feature engineering, exploratory data analysis, graph modeling, and machine learning Design and implement knowledge graphs to unify data across domains and support downstream AI/ML applications Apply graph algorithms and techniques to solve complex business problems, such as fraud detection and network analysis Develop and deploy supervised and unsupervised learning models to drive business outcomes Collaborate with business stakeholders, engineering, and partner teams to define problems, align project objectives, and communicate actionable insights Translate ambiguous and unstructured business problems into clear analytical solutions with measurable outcomes Drive end-to-end ownership of analytical tasks, from data wrangling to model deployment and performance monitoring Apply distributed machine learning and scalable statistical algorithms to handle large-scale data efficiently Qualifications & Skills Mandatory: 5+ years of hands-on experience as a Data Scientist, preferably in a fast-paced, data-driven environment 4+ years of experience with data querying (e.g., SQL) and scripting languages (e.g., Python) 3+ years of experience with Gen AI, machine learning/statistical modeling, including tuning and evaluating model performance Experience with graph data modeling, including tools/libraries like Oracle Graph DB, Neo4j, NetworkX, TigerGraph, GraphFrames, or RDF/SPARQL Strong business acumen and excellent verbal and written communication skills Good-to-Have: Experience working with distributed computing frameworks (e.g., Spark, Hadoop) Proven ability to drive insights and business decisions from large and complex datasets Hands-on experience building and maintaining knowledge graphs for applications in semantic search, data integration, or AI reasoning Experience with Graph-based anomaly detection techniques and fraud prevention systems Familiarity with Graph Neural Networks (GNNs) and other deep learning approaches for graph-structured data Experience in applied machine learning, integrating models into real-world systems Self-Assessment Questions To determine if you're a good fit for this role, consider the following questions: Can you describe a time when you had to communicate complex technical ideas to a non-technical audience? How did you approach the situation? How do you stay current with new technologies and advancements in the field of data science, and how do you apply that knowledge to drive business outcomes? Can you provide an example of a project where you had to work with large-scale data and apply distributed machine learning algorithms to drive insights? What were some of the challenges you faced, and how did you overcome them? How do you approach graph data modeling, and what tools or libraries have you used in the past to solve graph-structured data problems? Can you describe a situation where you had to drive end-to-end ownership of an analytical task, from data wrangling to model deployment and performance monitoring? What were some of the key challenges you faced, and how did you ensure the success of the project?

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We are seeking an experienced Senior Data Scientist to join our CSS team. As a Senior Data Scientist, you will play a key role in driving business growth by leveraging Generative AI, Machine learning, graph modeling, and statistical techniques to solve complex business challenges. You will work cross-functionally with business and partner teams to derive actionable insights and build scalable models using massive datasets.

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Career Level - IC3

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Job Summary We are seeking an experienced Senior Data Scientist to join our CSS team. As a Senior Data Scientist, you will play a key role in driving business growth by leveraging machine learning, graph modeling, and statistical techniques to solve complex business challenges. You will work cross-functionally with business and partner teams to derive actionable insights and build scalable models using massive datasets.

Key Responsibilities

• Demonstrate deep technical expertise in feature engineering, exploratory data analysis, graph modeling, and machine learning
• Design and implement knowledge graphs to unify data across domains and support downstream AI/ML applications
• Apply graph algorithms and techniques to solve complex business problems, such as fraud detection and network analysis
• Develop and deploy supervised and unsupervised learning models to drive business outcomes
• Collaborate with business stakeholders, engineering, and partner teams to define problems, align project objectives, and communicate actionable insights
• Translate ambiguous and unstructured business problems into clear analytical solutions with measurable outcomes
• Drive end-to-end ownership of analytical tasks, from data wrangling to model deployment and performance monitoring
• Apply distributed machine learning and scalable statistical algorithms to handle large-scale data efficiently

Qualifications & Skills

• Mandatory:
  • 5+ years of hands-on experience as a Data Scientist, preferably in a fast-paced, data-driven environment
  • 4+ years of experience with data querying (e.g., SQL) and scripting languages (e.g., Python)
  • 3+ years of experience with Gen AI, machine learning/statistical modeling, including tuning and evaluating model performance
  • Experience with graph data modeling, including tools/libraries like Oracle Graph DB, Neo4j, NetworkX, TigerGraph, GraphFrames, or RDF/SPARQL
  • Strong business acumen and excellent verbal and written communication skills
• Good-to-Have:
  • Experience working with distributed computing frameworks (e.g., Spark, Hadoop)
  • Proven ability to drive insights and business decisions from large and complex datasets
  • Hands-on experience building and maintaining knowledge graphs for applications in semantic search, data integration, or AI reasoning
  • Experience with Graph-based anomaly detection techniques and fraud prevention systems
  • Familiarity with Graph Neural Networks (GNNs) and other deep learning approaches for graph-structured data
  • Experience in applied machine learning, integrating models into real-world systems

Self-Assessment Questions To determine if you're a good fit for this role, consider the following questions:

1. Can you describe a time when you had to communicate complex technical ideas to a non-technical audience? How did you approach the situation?
2. How do you stay current with new technologies and advancements in the field of data science, and how do you apply that knowledge to drive business outcomes?
3. Can you provide an example of a project where you had to work with large-scale data and apply distributed machine learning algorithms to drive insights? What were some of the challenges you faced, and how did you overcome them?
4. How do you approach graph data modeling, and what tools or libraries have you used in the past to solve graph-structured data problems?
5. Can you describe a situation where you had to drive end-to-end ownership of an analytical task, from data wrangling to model deployment and performance monitoring? What were some of the key challenges you faced, and how did you ensure the success of the project?