Sonakshi Pandey is currently focused on the Data Analytics stack of the Google Cloud. She helps solve big data problems for Enterprise customers using the Google Cloud Platform.

She is a woman in Tech and has worked for the giant Tech Giants like Amazon and Google. She started her career as a Software Engineer, where She was used to putting on her headphones and coding for 8 hours straight. After three years of being confined to her cubicle, she put herself out there and tried a totally opposite role. She transitioned from Software Development to Technical Sales and is confident that she was born to do this! 

Can you tell us about your AI journey? 

My passion for AI was fueled when I began working as a software engineer on the forecasting team at Amazon. My team was crucial in stocking warehouses, preventing those dreaded "out-of-stock" messages. This platform relied heavily on powerful machine learning models, and I was responsible for building and maintaining the entire infrastructure they ran on.

Part of my role was managing and optimizing Hadoop and Spark clusters as a platform for ML models. Apart from this, I also developed Spark applications to extract valuable insights. One critical project involved building a microservice that quickly and efficiently detects forecast outliers, such as data anomalies or significant errors. This reduced data scientists' operational workload by 80% and slashed the time needed to extract actionable insights by 90%.

Witnessing how my work directly contributed to the efficiency and accuracy of the forecasting workflow was incredibly rewarding. It solidified my passion for AI and its potential to solve real-world problems.

What is your area of expertise in AI, and what made you choose it?

In the world of AI, my expertise lies around the data transformation phase within the AI pipeline. My role involves collaborating with organizations to facilitate data migrations, filtering, and transformation of raw data, ensuring it is suitable for running AI/ML models that provide valuable insights.

A critical dimension of my responsibilities is the establishment of repeatable data pipelines. This includes designing efficient systems that automate the movement and pre-processing of data, streamlining the overall AI workflow. Moreover, a critical focus is placed on data governance to uphold the security and compliance aspects of the data used in AI pipelines. Mainly, considerations are made for personally identifiable information (PII) and adherence to regulatory requirements.

Recognizing that "accurate data" is the cornerstone of any effective AI solution, I am motivated by the fundamental role played by data in the success of AI transformations. This necessity for precision and reliability in data is the reason behind my specialization in data analytics. Witnessing how accurate and well-prepared data is the bedrock for successful AI implementations inspires me to grow in this domain.

How did generative AI impact your field of work? 

Generative AI has emerged as a disrupter, reshaping various industries, including where I work. My close collaboration with customers in building data AI ML solutions on the Google Cloud has provided me a front-row seat to the disruptive influence of generative AI in the technological landscape.

With the boom of generative AI, there has been a surge in interest among companies keen to explore its potential. Organizations are eager to harness generative AI to enhance employee efficiency, automate processes, and maintain a competitive edge in the market.

Personally, this shift has significantly impacted my work dynamic. I dedicate more time to learning about different generative AI models, immersing myself in hands-on experiences, and actively participating in creating solutions. The objective is clear – to showcase and demonstrate how generative our customers can effectively leverage AI to elevate the accuracy and efficiency of their work.

The introduction of generative AI has altered the technological landscape and prompted a continuous learning journey for professionals like myself. It's an exciting phase where staying updated on the latest advancements in generative AI becomes integral to providing valuable insights and solutions to our customers, pushing them toward more incredible innovation and operational excellence.

Describe some challenges you have faced in reaching where you are now.

Navigating the path to my current position has been marked by several challenges, particularly as a "woman" entering the domain of AI. In the early stages, I was surrounded predominantly by male counterparts who often projected an air of self-assuredness. The scarcity of female role models in the field compounded the challenge, leading to instances where I struggled with imposter syndrome – a strong feeling of not deserving a place in the professional landscape.

One significant hurdle I encountered was the struggle to assert myself adequately. Due to the prevailing dynamics, I often held back, not voicing my ideas as assertively as needed. This hesitation hindered my ability to contribute fully to my role and give my best to the job.

A turning point in overcoming these challenges came when I sought a mentor. The guidance and support provided by my mentor played a pivotal role in shaping my career trajectory. Confronting imposter syndrome head-on, my mentor taught me strategies to navigate day-to-day challenges effectively. I learned valuable lessons on cultivating confidence and expressing my ideas assertively. This experience impacted my professional journey and transformed me from a hesitant presence in the room to an engineer recognized and respected by my peers.

Though challenging, the journey has been one of growth and empowerment, highlighting the importance of mentorship and self-advocacy in overcoming barriers and achieving success in AI.

Do you see enough female leadership roles in corporates? In your opinion, what should change?  

The presence of female leadership roles in corporate settings is still lacking, especially in the tech industry, where there is a notable gender disparity. While there are many women in tech, most do not occupy leadership positions or positions of authority.

Companies must proactively embrace and champion inclusive hiring practices to address this imbalance. Recruitment processes must be reexamined to ensure fairness and impartiality, promoting talent selection from diverse backgrounds.

A significant shift is needed in promoting women at entry levels and throughout their careers. This involves having more women allies at high levels within organizations. Merely increasing the number of women in junior engineering roles is not enough. Active promotion and encouragement are necessary at every stage of a woman's career journey.

Investing in leadership training and development programs tailored for women is crucial. Such programs are pivotal in equipping women with the necessary skills and fostering the confidence to step into leadership roles with competence and assurance. Furthermore, women leaders should actively mentor and encourage young women to pursue leadership roles.

Establishing Employee Resource Groups (ERGs) specifically for and by women can create a supportive space where ongoing issues can be shared and collective learning can occur. These groups serve as platforms for guidance, networking opportunities, and advocacy, offering valuable support for women navigating the path to leadership roles.

The collective effort of organizations, leaders, and individuals is critical to bringing a cultural shift that actively promotes and encourages women at all career levels.

What do you want to say to women who wish to build careers in AI and other tech-related fields? 

For women aspiring to build careers in AI and other tech-related fields, here are some valuable pieces of advice:

Community is Key:

Building a career in AI doesn't have to be a lonely journey. Seek out a community of women where you feel a sense of belonging and comfort. In such spaces, you can freely voice your opinions, discuss challenges, and seek help when needed. If you can't find a community near you, consider taking the initiative to create one. Start an inclusive platform that brings together women in AI, fostering collaboration and support.

Find a Mentor:

A mentor can be a guiding light on your career path. Look for someone who may not be directly in your field but has experienced the challenges you might encounter. A mentor can provide valuable advice, share insights, and offer a broader perspective on navigating the tech industry. Having a mentor can be instrumental in overcoming obstacles and making informed career decisions.

Share Your Journey:

Courageously speak up and share your journey, no matter the difficulties you face or the challenges encountered in the workplace. Doing so contributes to a collective narrative that can inspire and resonate with others. You never know – your story might help someone facing similar situations, and together, you may find creative solutions to common challenges. 

Don't underestimate the impact of your voice in shaping a more inclusive and supportive environment.

By finding spaces for collaboration, seeking mentorship, and sharing your journey, you enhance your personal growth and contribute to women's empowerment in the tech industry. 

Your voice matters, and your experiences can inspire and guide others on their paths.