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Data Science

Radar—Breaking Through The Noise: Starting a Career in Data in 2022

July 2022

Your Presenter(s)

Sadie St. Lawrence

CEO & Founder at Human-Machine Collaboration Institute at Women in Data

Sadie St. Lawrence is the Founder and CEO of the Human Machine Collaboration Institute (HMCI), where she leads pioneering research, education, and advising efforts aimed at optimizing human and machine interaction in the AI-driven era of knowledge work. She also founded Women in Data™, an international non-profit organization represented in 55 countries with a thriving community of over 70,000 data professionals. Under her leadership, Women in Data was recognized as a Top 50 Leading Non-Profit and the premier community for Women in AI and Tech in 2021.With academic foundations in piano performance, psychology, and data science, Sadie’s career spans from neuroscience research to over a decade leading data science and AI strategy teams at organizations such as VSP and Accenture. Her contributions to the field have earned her recognition as one of DataIQ’s Top 100 Most Influential People in Data (2024) and Dataleum’s Top 30 Women in AI (2022)Sadie actively contributes to national initiatives as a member of the White House Council for Data and AI Training and the OpenAI Research Community. Her passion for education has driven her to train over 700,000 individuals through data science and AI courses at UC Davis, Coursera, and LinkedIn Learning.

Summary

The broad range of data careers offer countless opportunities but also brings the challenge of intense competition. Sadie St. Lawrence, founder of Women in Data, discussed this issue during the webinar, explaining how individuals can shape their careers in the data industry. She stressed the importance of understanding one's motives and shared strategies for standing out in a crowded field of job titles and educational paths. She shared her experiences, emphasizing the importance of self-awareness, engagement with the community, and continuous learning. The session also covered the trend of hiring based on skills, the importance of understanding personal strengths, and practical steps to build a successful data career.

Key Takeaways:

Understand your motives to guide your career change to data science.
Engage in a cycle of learning, applying, sharing, and repeating to enhance your data science skills.
Engage with communities to expand your network and opportunities.
Focus on building and showcasing practical skills over formal degrees to adapt to the trend of skill-based hiring.
Be ready for the emerging trend of hiring based on skills.

Deep Dives

Understanding Your Motives

A foundational step in making a transition to a data science career is understanding and defining your motives. Sadie stressed that knowing your purpose guides your decisions and helps you persevere through challenges. She suggested activities like writing a vision statement and detailing a perfect workday to solidify this purpose. For example, Sadie's vision of creating a compassionate, connected world through technology guides her professional endeavors. This clarity aids in filtering job opportunities but also fuels motivation and resilience. "Your vision statement can be whatever you want it to be, but you should know what it is and it's personal to you," Sadie advised.

Standing Out in the Crowd

The data field is filled with various job titles and learning paths, which can be daunting. Sadie's approach to managing this complexity focuses on self-discovery and strategic planning. She urged participants to identify their existing skills and align them with targeted job skills to ease their transition to desired roles. Sadie also highlighted the importance of not starting from scratch, recognizing the value of past experiences and skills. "If you truly want to stand out from the crowd, you have to be yourself," she asserted, encouraging individuals to embrace their unique strengths.

Community Engagement and Networking

Sadie pointed out the vital role of community engagement and networking in career advancement. She described the benefits of leveraging one's network, stating, "Your network is your net worth." Building connections within the data community provides access to support, resources, and opportunities. Sadie encouraged active participation in communities, emphasizing the reciprocal nature of value: offering assistance and knowledge can lead to receiving the same in return. Networking not only aids in job searches but also in gaining insights into industry trends and skill demands.

Preparing for Skill-Based Hiring

The trend towards hiring based on skills is gaining momentum, as noted by Sadie. Companies like IBM and Microsoft are increasingly valuing skills over traditional educational credentials. Sadie encouraged participants to focus on developing and showcasing practical skills, such as coding, communication, and analytical abilities. She recommended identifying companies that prioritize skills and adjusting resumes and applications accordingly. This trend allows for greater accessibility to data roles for non-technical professionals. "What I would do is try and look for those companies that prioritize skills in their evaluation criteria," Sadie advised, highlighting this as a strategic approach to break into the field.