Updated: Aug 18, 2026
No. of Questions: 87 Questions & Answers with Testing Engine
Download Limit: Unlimited
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| Certification Vendor: | DASCA (Data Science Council of America) |
| Exam Name: | Senior Data Scientist Certification Exam |
| Exam Number: | SDS |
| Exam Price: | USD 950 |
| Exam Duration: | 100 minutes |
| Real Exam Qty: | 85 |
| Exam Format: | Multiple-choice single-answer, Multiple-choice multiple-answer |
| Passing Score: | 65% |
| Available Languages: | English |
| Related Certifications: | Principal Data Scientist (PDS™) Senior Big Data Engineer (SBDE™) Senior Big Data Analyst (SBDA™) |
| Certificate Validity Period: | 5 years |
| Recommended Training: | DataScienceSkool™ Official Learning Resources |
| Exam Registration: | Official Registration Portal |
| Sample Questions: | DASCA SDS Sample Questions |
| Exam Way: | Online, remotely proctored via ExamStrong™ platform; available globally |
| Pre Condition: | Bachelor's degree + 4–5 years relevant experience; or Master's degree + 3–4 years experience in data science, analytics, or related fields |
| Official Syllabus URL: | https://www.dasca.org/data-science-certifications/senior-data-scientist |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: MLOps & Production Deployment | 15% | - Model lifecycle management, monitoring, and maintenance - Model governance, security, and reliability - DevOps integration, automation, and CI/CD |
| Topic 2: Big Data Ecosystems & Scalable Systems | 20% | - Scalability, performance, and optimization - Distributed computing frameworks and cloud platforms - Data storage, processing pipelines, and governance |
| Topic 3: Advanced AI & Generative AI | 20% | - Responsible AI, ethics, fairness, transparency, and compliance - Generative AI techniques, use cases, and limitations - Deep learning, neural networks, and foundation models |
| Topic 4: Data Science Applications in Business | 20% | - Data science strategy and enterprise alignment - Measuring and demonstrating ROI of data science initiatives - Translating business requirements into data science problems |
| Topic 5: Foundational Methods & Frameworks | 25% | - Data preparation, feature engineering, and quality assurance - Advanced statistics, probability, and experimental design - Machine learning algorithms, selection, and evaluation |
1. Which of the following is NOT a part of Internal Process Optimization?
A) None of the above
B) Business Monitoring
C) Business Metamorphosis
D) Business Optimization
E) Business Insights
2. Which of the following is the most important part of Hadoop?
A) MapReduce Framework
B) Spark Framework
C) Hadoop Distributed File System (HDFS)
D) Both B and C
E) Both A and B
3. What is TRUE for "rehashing"?
A) Key/value pairs from the original table can be inserted into the new, larger one
B) Allocate a new, larger hash table in memory
C) Both A and B
D) It requires a new hash function, which maps values into a larger range of integers
E) All of the above
4. 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 100 times faster in memory and 10 times faster on disk in comparison to the traditional Hadoop MapReduce
C) 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
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
5. Which of the following can visualize variations in the base data, which can be used to identify outliers in the data for further investigation?
A) None of the above
B) Histogram
C) Box Plots
D) Trend Analysis
E) Scatter Plot
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: E | Question # 3 Answer: E | Question # 4 Answer: B | Question # 5 Answer: C |
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