DASCA Senior Data Scientist : SDS

  • Exam Code: SDS
  • Exam Name: Senior Data Scientist
  • Updated: Aug 22, 2026
  • Q&As: 87 Questions and Answers

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DASCA SDS Exam Syllabus Topics:

SectionWeightObjectives
Machine Learning at Scale25-30%- Unsupervised Learning
  • 1. Clustering Algorithms
  • 2. Dimensionality Reduction
  • 3. Anomaly Detection
- Supervised Learning
  • 1. Time Series Forecasting
  • 2. Support Vector Machines
  • 3. Ensemble Methods
- Deep Learning Fundamentals
  • 1. Recurrent Networks
  • 2. Neural Networks
  • 3. Convolutional Networks
Data Visualization and Communication10-15%- Visualization Principles
  • 1. Storytelling with Data
  • 2. Dashboard Design
- Tools and Technologies
  • 1. Python Visualization Libraries
  • 2. Tableau/Power BI
Big Data Engineering15-20%- Cloud Computing for Data Science
  • 1. AWS/Azure/GCP Services
  • 2. Serverless Architectures
  • 3. Containerization
- Distributed Computing
  • 1. Hadoop Ecosystem
  • 2. Data Pipelines
  • 3. Apache Spark
Foundations of Data Science15-20%- Data Science Ethics
  • 1. Privacy and Confidentiality
  • 2. Bias and Fairness
  • 3. Transparency and Explainability
- Data Science Lifecycle
  • 1. Problem Formulation
  • 2. Model Building and Evaluation
  • 3. Data Collection and Preparation
  • 4. Deployment and Monitoring
Advanced Statistical Modeling20-25%- Regression Analysis
  • 1. Regularization Techniques
  • 2. Generalized Linear Models
  • 3. Linear and Logistic Regression
- Statistical Inference
  • 1. Hypothesis Testing
  • 2. Bayesian Methods
  • 3. Confidence Intervals

DASCA Senior Data Scientist Sample Questions:

1. Which of these are open-source column-oriented databases?

A) All of the above
B) HBase
C) Cassandra
D) Both A and B
E) Accumulo


2. Which of the following is NOT used to implement Agile?

A) Kanban
B) Scrum
C) Extreme Programming (XP)
D) Six Sigma


3. Machine learning can be categorized as:

A) Reinforcement learning
B) All of the above
C) Supervised learning
D) Unsupervised learning


4. Which of the following is NOT a valid section of Big Data Strategy document?

A) Business strategy
B) Business decisions
C) Key decisions
D) Key business entities
E) Key business initiatives


5. Which of the following statements is correct?

A) Apache claimed that Spark is able to run parallel jobs 50 times faster in memory and 5 times faster on disk in comparison to the traditional Hadoop MapReduce
B) Apache claimed that Spark is able to run parallel jobs 1000 times faster in memory and 100 times faster on disk in comparison to the traditional Hadoop MapReduce
C) Apache claimed that Spark is able to run parallel jobs 100 times faster in memory and 10 times faster on disk in comparison to the traditional Hadoop MapReduce
D) Apache claimed that Spark is able to run parallel jobs 10 times faster in memory and 100 times faster on disk in comparison to the traditional Hadoop MapReduce


Solutions:

Question # 1
Answer: A
Question # 2
Answer: D
Question # 3
Answer: B
Question # 4
Answer: B
Question # 5
Answer: C

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