The Challenges of Being a Data Scientist

It stands to reason that there have been numerous challenges, given how quickly the technology industry has evolved in recent years. Business leaders have navigated through their own set of challenges to successfully derive multiple disruptive solutions.

Puspanjali Sarma, Technology Practice Lead at Rackspace Technology, interacted with Analytics India Magazine about what it’s like to be a modern technology leader, overcoming challenges one at a time.

With more than 13 years of experience leading digital transformation initiatives and offering analytics consulting, Puspanjali Sarma is a creative leader in the tech industry. She has designed data strategies for Fortune 500 companies as well as start-up businesses in domestic and international markets, using a combination of data and artificial intelligence. 

Currently, Puspanjali Sarma leads Data and AI Practice for UK, Europe, and Middle East customers, in delivering business value through Data, Machine Learning and Artificial Intelligence. 

About her daily life, Puspanjali says she spends her days brainstorming with industry leaders in devising Data and AI strategies along with mentoring aspirants to be data professionals.

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Life as a Principal Data Scientist

By giving a structural overview of the multi-cloud company, Puspanjali Sarma says that professional services through their businesses are divided into three regions—EMEA, APAC, and the US, which is headquartered in Austin, Texas. Puspanjali is the Practice Lead, or the head of the practice for the EMEA region. 

“As a Principal Data Scientist, I am responsible for large, scientifically complex projects and break them down into manageable hypothesis and experiments to inform, functional specifications, then deliver features in a successful and timely manner is expected. As part of my daily work streams, I am responsible for identifying, scoping, clearing data and science-related bottlenecks, provide escalation management, anticipate and make trade-offs, and balance business needs versus scientific and technical constraints.”

Puspanjali says that it’s routine for her to interact with the sales team and regional heads—with the focus on understanding how the business moves. The leadership team focuses on whether requirements are met adequately by proposing solutions and engaging with the customers in terms of data. 

“My other responsibilities include taking care of end-to-end processes, streamlining the processes of the practice, oversee delivery the projects, PnL management etc.”

Puspanjali hopes to ensure market awareness about not only the team’s cloud services products, but also their data and AI services—a ‘must have’ requirement across industries. 

“Database administrators are becoming data engineers. The data engineers are becoming architects and to move to the levels of senior architect or the principal architect. My practice is stable from that perspective. My next goal for the practice and organization is to build and execute roadmap with the leadership team in Rackspace EMEA that how we should be progressing in terms of designing as our go-to market strategy.”

Battling hurdles in AI journey

Puspanjali Sarma says that it wasn’t effortless to land her current role in the industry. 

“While being a fresher back in 2008, I was a victim of recession, which was very bad at the time. I got an offer from one of the largest service providers Satyam Computers, who was a leader in the market for data analytics at the time in that era. So, because of the scam, they revoked my offer, and I was without a job.”

Puspanjali then worked on a contract basis as a data engineer, developing end to end data warehouses in designing, developing, and supporting. Her keen interest to understand SQL databases in college helped her drive her curiosity in the domain. 

“The journey from an Engineer to a Woman Leader had not been an easiest one for me. I always had to work double to prove my worth. I surely have done well being where I want to be, but what I really want to do is to bring change to the organisations in giving women fair opportunity in tech.”

Highlighting the challenges while solving business problems she further said—“Challenges can be from different areas. It can be a data problem or even a process problem—even issues in an overall system integration. The question is, how can you build the right solution which is going to give you output that will impact your business decisions.”

The best way to solve a data problem is to always backtrack and see the source of the problem and untie knots one after another to resolve it. “People view dealing with graphs as boring task, so extensive data exploration step is skipped. In reality, if the machine learning model is not giving the right output, it is because there is a problem with the data. That’s the approach I always took. And that’s actually how I have been working since the beginning of my career as data practitioner! I believe in a data-centric, not model-centric approach!”

Diversity remains a myth 

​​” People talk about women in technology, but in reality, it remains a myth.” Puspanjali feels that women must receive more acknowledgement in terms of their skill and potential, rather than being categorised into buckets due to their status. 

“Women are always seen as inferior in terms of technical capability. By hiring female members in the team, I’m trying to bring diversity in my team. I see that a lot of organisations lack the growth mindset in changing the organizational culture, not knowing when it is time to change with changing times.”

Puspanjali is a Women Tech makers Ambassador at Google, Hyderabad who aims on inspiring women from different communities to build their career in tech. 

On addressing gender bias in organisations, she says, “Women have to step up by putting ourselves in front to take the lead. If you don’t know something, say yes and do it. It’s all about getting the opportunity. It’s not about doing the tasks. If you don’t know Java, you can learn and implement it. If you don’t understand how to code, one can learn and implement it in application design. We should focus on potential of a candidates, not gender. The ultimate goal should be to provide equal opportunities to all and work on bringing equality all terms at organisations.”

Future outlook for tech industry

Puspanjali shares her view on the outlook for the industry in the coming years, citing that using the algorithms should not be the only focus. 

“Firstly, people are stuck on software development principles for data science or ML, and they have to come out of it. Everything has become automated in terms of data science, so that you don’t have to write pages of code to implement a solution for machine learning algorithm. Explainable AI is next in line of popularity.”

Puspanjali Sarma believes that data centric approach is going to take the centre stage, with model-centric approach being the secondary or tertiary requirement—as models are constant.

She further adds that responsible AI and ML Ops are likely to gain more prominence because implementation of AI impacts users directly. “AI implementation impacts lives. If you are not designing your AI system properly, the person might get killed in a self -driving car. If you’re not giving the right medication to a sick person through the AI bots, then the person might be in danger, right? So, responsible AI is going to take the centre stage in terms of producing the right kind of AI application.” Puspanjali Sarma concluded by emphasising that the next generation of AI and ML is certain to be on Cloud.