Unlock the Secrets to Fast-Tracking Your Data Career with Srimukessh Subramanian
- S4E16
- 14:09
- March 25th 2024
Are you a data leader eager to accelerate your professional growth and make a bigger impact? In this episode, we sit down with Srimukessh Subramanian, Finance Data Analyst at Wise, who shares his journey from engineering to data and reveals the key skills that have propelled his career forward.
Discover how you can:
Master the technical skills that will make you indispensable, including SQL, Python, and the growing importance of dbt knowledge
Develop the crucial non-technical skills, such as effective communication and storytelling, to influence stakeholders and drive change
Leverage pet projects to showcase your abilities, enhance your skills, and secure your dream job in data
Navigate the transition from data analyst to product manager and other creative roles in data
Continually improve your skills and stay ahead of the curve in a rapidly evolving field
Whether you're a seasoned data leader or just starting your journey, this episode is packed with actionable insights and advice to help you supercharge your career. Srimukessh's unique perspective, from his background in engineering to his current role as a finance data analyst, offers valuable lessons for anyone looking to make their mark in the world of data.
MLTeam Success
Welcome to ML Team Success — the show for ML engineers, data scientists, and MLOps practitioners who want to actually ship AI that works in production.
I'm Ross Webb. I've led data product teams and ML engineering teams at places like Amazon and Just Eat, building platforms used by thousands of professionals. I've seen what works, what breaks, and why 90% of ML projects never make it to production.
Each episode: real conversations with practitioners who are solving the hard problems — MLOps, model deployment, inference at scale, data pipelines, and the shift to AI engineering and agentic systems.
No theory for theory's sake. No hype. Just the stuff that matters when you're trying to get models into production and keep them there.
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