AdaSci’s Chartered Data Scientist™(CDS) is one of the most prestigious certifications a Data Scientist can get hold of. The qualified candidates demonstrate a thorough understanding of advanced analytics and data science skills. CDS™ program – conducted by ADaSci, is a self-study programme that has been helping data scientists to get the extra edge in a highly competitive ecosystem.
CDS examination is a global standard exam to test the 360 degree of the skill-sets one has. Srikanth Phalgun Pyaraka is amongst the top candidates who cracked CDS. Analytics India Magazine got in touch with Srikanth Phalgun Pyaraka to know more about his experience of writing the examination and being a CDS charter holder.
AIM: Could you tell us about your professional and educational background?
Srikanth: I did my engineering in Computer Science stream from Institute of Aeronautical Engineering College in 2007. After graduation, I joined Verizon and have been with the organisation since then. I have an overall experience of 13 years, out of which I have worked for more than eight years in the field of Data Analytics. One of the perks of working as a software developer and analytics consultant is the exposure to work with different business units, teams and departments. As a data science practitioner, I have held various roles as Data/ML engineer. I’m a NLP/Computer Vision enthusiast. I also train and mentor data science aspirants.
Currently, I am leading the Data Analytics team as lead Data Scientist/Consultant for a supply chain organisation responsible for developing strategies for effective data analytics and implementing analytics solutions for strategic sourcing. This includes spending analytics, financial health assessment, market intelligence, digital transformation, process improvements and automation to build frameworks that enable data-driven decision making to business stakeholders. Previously, I have also worked on projects related to fraud analytics, telecom billing analytics, strategic sourcing, finance and as a tool or application developer.
AIM: How did your journey begin in Data Science? How has it been so far?
Srikanth: I was working on telecom billing applications. My responsibilities as a billing analyst was to find anomalies in data, explore opportunities for process improvement, and develop tools that automate that process. I spent a reasonable amount of time crunching, analysing, cleaning and preprocessing data to find the exact reason for certain issues. Meanwhile, I developed more than 30 tools, reports and applications. Unknowingly, I was doing part of data science exactly. My curiosity increased, and I started learning techniques and methodologies in 2012.
Furthermore, I got opportunities to work on many projects on data science, deep learning, NLP, computer vision under the guidance of best mentors. This boosted my confidence to solve business problems where traditional approaches have hit roadblocks. Today, I believe organisations are more mature. They have started to understand that economic driven business transformation requires efficiency in leveraging the technology and not the disruptiveness of the technology itself. This applies to all buzzwords that people use, whether it’s AI-driven or anything else. It’s important to “think differently” and in the process to move from technology-driven initiatives to business-driven initiative approaches.
AIM: What were the initial challenges you faced in the field? How did you overcome them?
Srikanth: While working with business stakeholders to integrate data and analytics into business models, we have faced multiple challenges. One of the significant challenges that we face in most organisations is Business Intelligence reporting to the next level of enabling predictive or prescriptive analytics decision making. This is what we call an analytic chasm. Organisations should tend to move from the analytics chasm with the help of change in the mindset of decision-makers. The main focus should be on leveraging technology to competitive power differentiation and not competitive parity. Greater emphasis should be to build infrastructure and data analytics environments to support data-driven business initiatives. Focus on key business initiatives and break them down into supporting decisions, questions and metrics and build Data science use cases to support data-driven targeted Business Initiatives.
AIM: How did you come to know about the CDS™ examination? How many hours did you dedicate each day to master the domain?
Srikanth: I was looking for vendor-neutral data science exams to benchmark my knowledge at International standards in general. I generally follow analytics magazines and newsletters to keep myself up to date. I came across a newsletter mentioning the CDS program, and after some research, I found out that it is the right fit for my requirement as it tests end to end in all disciplines. I have spent my weekdays revising familiar topics and weekends studying new issues. On an average, it’s almost about 10 to 15 hours per week, which I think is sufficient for the examination. However, it also varies from person to person in general.
AIM: How did you prepare for the exam? Since when did you begin your preparation for the exam?
Srikanth: As it is a self-study program. It requires a lot of commitment and dedication to complete the same—my suggestion to get a strict schedule before the exam date, based on your convenience. It would be best if you plan your preparation accordingly. I had a clear strategy to assess topics and gather resources required to attain mastery. My approach is to categorise my solid areas and gaps. Initially, I started revising my vital area, which covered most topics and made notes of issues that needed additional study. I had to put 2 to 3 months of structured effort to make sure most of the curriculum is covered, giving confidence in exam readiness.
AIM: What was your approach to crack the exam? How do you think CDS will help in your professional journey as a data scientist?
Srikanth: Chartered Data scientist designation is the highest distinction in the data science profession. The exam looks for skills including computer programming, including R and Python; Mathematics, especially statistics and probability; Analytical Methods such as EDA, ML algorithms; Advance Analytics including deep learning, computer vision, NLP; and Business Analytics at international standards. These are the core skills for a good data scientist to solve complex real-time problems. The CDS program will help to benchmark competency in these skills, and it helped me be more competitive in this industry and perk to be in a great network of expert data scientists to learn and share knowledge.
Here are a few quick tips:
- As the exam date approaches, it’s good to relax and be confident in the effort you are putting in.
- The exam is designed with the option to choose which topic to go first with. So, start with familiar or the topics which you are confident about.
- With more time on hand, you can then move to unfamiliar ones.
- Don’t rush. Answer those which you think are correct.
- Use the general process of eliminating wrong answers, and in case you are facing problems with the question, mark that question to revisit and, if necessary, make an educated guess.
AIM: How has been your experience after becoming a Chartered Data Scientist? What does a typical day look like for you?
Srikanth: It is a great feeling as it boosts my confidence. During preparation, It helped me fill skill gaps by unlearning and relearn many things that would eventually help me perform better in solving complex problems. I work with business stakeholders to design and create frameworks to enable them with data-driven decision making. It includes converting business problems into analytical problems, extracting and analysing appropriate data and providing analytical solutions.
The solution may vary based on business problem use cases as some require simple reports other need complex models. My typical day is not the same, as it varies. I usually have to spend a reasonable amount of time brainstorming with brilliant minds on specific problems in different perspectives and strategies to derive analytics solutions.
AIM: What books and other resources have you used in your journey to CDS?
Srikanth: I will start from the beginning and suggest referring to the “CDS Candidate Guide” to get more information about the CDS exam and curriculum/reference textbooks. Once registered for the exam, you can access CDSBok. This Chartered Data Scientist (CDS) examination book of knowledge (BoK) covers the CDS curriculum and explains the topics in detail that will be a foundation for exam preparation. Assess your ability based on CDSBoK and note sections that are your strong area and skill gaps.
Assessment will help you plan your preparation and also help to decide when to take the exam, like in three or six months. After Assessment, schedule your exam date, start practice accordingly, and reassess until skill gaps become your strong area. I have followed all suggested books for CDS exam preparation. Apart from that learning from my work experience and online resources, Analytics blogs helped me clearly understand certain concepts.
AIM: What do you think is the wrong conception about this field among aspirants? How was your overall CDS program experience?
Srikanth: One of the most common misconceptions among people has been that the field is only for programmers, math geeks or PhD holders. Thanks to a few job ads that made it impossible to meet requirements to get into this field. Anyone can get into this field. All you need is to select the data driven problem and try to solve it and learn in that process. Stay away from buzzwords. My personal take is this field is open for problem solvers, quick learners, curious mindsets.
My overall experience was great, indeed it’s like one of my wishes coming true. Starting from enrolling for the CDS program, exam preparation and taking tests gave me the opportunity to continuously learn, unlearn and re-learn. Keeping me on my toes!!