DataTalks.Club

In this talk, Xia He-Bleinagel, Head of Data & Cloud at NOW GmbH, shares her remarkable journey from studying automotive engineering across Europe to leading modern data, cloud, and engineering teams in Germany.We dive into her transition from hands-on engineering to leadership, how she balanced family with career growth, and what it really takes to succeed in today’s cloud, data, and AI job market.TIMECODES:00:00 Studying Automotive Engineering Across Europe08:15 How Andrew Ng Sparked a Machine Learning Journey11:45 Import–Export Work as an Unexpected Career Boost17:05 Balancing Family Life with Data Engineering Studies20:50 From Data Engineer to Head of Data & Cloud27:46 Building Data Teams & Tackling Tech Debt30:56 Learning Leadership Through Coaching & Observation34:17 Management vs. IC: Finding Your Best Fit38:52 Boosting Developer Productivity with AI Tools42:47 Succeeding in Germany’s Competitive Data Job Market46:03 Fast-Track Your Cloud & Data Career50:03 Mentorship & Supporting Working Moms in Tech53:03 Cultural & Economic Factors Shaping Women’s Careers57:13 Top Networking Groups for Women in Data1:00:13 Turning Domain Expertise into a Data Career AdvantageConnect with Xia- Linkedin - https://www.linkedin.com/in/xia-he-bleinagel-51773585/- Github - https://github.com/Data-Think-2021- Website - https://datathinker.de/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

In this talk, Anusha Akkina, co-founder of Auralytix, shares her journey from working as a Chartered Accountant and Auditor at Deloitte to building an AI-powered finance intelligence platform designed to augment, not replace, human decision-making. Together with host Alexey from DataTalks.Club, she explores how AI is transforming finance operations beyond spreadsheets—from tackling ERP limitations to creating real-time insights that drive strategic business outcomes.TIMECODES:00:00 Building trust in AI finance and introducing Auralytix02:22 From accounting roots to auditing at Deloitte and Paraxel08:20 Moving to Germany and pivoting into corporate finance11:50 The data struggle in strategic finance and the need for change13:23 How Auralytix was born: bridging AI and financial compliance17:15 Why ERP systems fail finance teams and how spreadsheets fill the gap24:31 The real cost of ERP rigidity and lessons from failed transformations29:10 The hidden risks of spreadsheet dependency and knowledge loss37:30 Experimenting with ChatGPT and coding the first AI finance prototype43:34 Identifying finance’s biggest pain points through user research47:24 Empowering finance teams with AI-driven, real-time decision insights50:59 Developing an entrepreneurial mindset through strategy and learning54:31 Essential resources and finding the right AI co-founderConnect with Anusha- Linkedin - https://www.linkedin.com/in/anusha-akkina-acma-cgma-56154547/- Website - https://aurelytix.com/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

Join Andrey Vasnetsov, co-founder and CTO of Qdrant, as he shares the journey of building a developer-focused vector database during the pandemic. Slava Dubrov from HubSpot dives into AI Signals, discussing the power of embeddings in contextual recommendations. Marina Ariamnova of SumUp reveals her innovative LLM assistant that rapidly translates natural language to SQL, transforming analytics workflows. Lastly, Evgeniya Sukhodolskaya explores retrieval research and education at Qdrant, touching on the future of AI in developer tooling.

Hugo Bowne-Anderson, an independent AI consultant and educator, shares insights from his journey from academia to advising major companies like Netflix and Meta. He discusses how to build reliable AI systems, focusing on practical tips for prompt evaluation and dataset design. Hugo emphasizes the importance of structuring teams for successful AI adoption and offers strategies to avoid common pitfalls like prompt overfitting. Listeners will learn about debugging tools and the evolution of proactive AI agents that enhance productivity in everyday workflows.

In this talk, Sebastian, a bioinformatics researcher and software engineer, shares his inspiring journey from wet lab biotechnology to computational bioinformatics. Hosted by Data Talks Club, this session explores how data science, AI, and open-source tools are transforming modern biological research — from DNA sequencing to metagenomics and protein structure prediction.You’ll learn about: - The difference between wet lab and dry lab workflows in biotechnology - How bioinformatics enables faster insights through data-driven modeling - The MCW2 Graph Project and its role in studying wastewater microbiomes - Using co-abundance networks and the CC Lasso algorithm to map microbial interactions - How AlphaFold revolutionized protein structure prediction - Building scientific knowledge graphs to integrate biological metadata - Open-source tools like VueGen and VueCore for automating reports and visualizations - The growing impact of AI and large language models (LLMs) in research and documentation - Key differences between R (BioConductor) and Python ecosystems for bioinformaticsThis talk is ideal for data scientists, bioinformaticians, biotech researchers, and AI enthusiasts who want to understand how data science, AI, and biology intersect. Whether you work in genomics, computational biology, or scientific software, you’ll gain insights into real-world tools and workflows shaping the future of bioinformatics.Links:- MicW2Graph: https://zenodo.org/records/12507444- VueGen: https://github.com/Multiomics-Analytics-Group/vuegen- Awesome-Bioinformatics: https://github.com/danielecook/Awesome-BioinformaticsTIMECODES00:00 Sebastian’s Journey into Bioinformatics06:02 From Wet Lab to Computational Biology08:23 Wet Lab vs Dry Lab Explained12:35 Bioinformatics as Data Science for Biology15:30 How DNA Sequencing Works19:29 MCW2 Graph and Wastewater Microbiomes23:10 Building Microbial Networks with CC Lasso26:54 Protein–Ligand Simulation Basics29:58 Predicting Protein Folding in 3D33:30 AlphaFold Revolution in Protein Prediction36:45 Inside the MCW2 Knowledge Graph39:54 VueGen: Automating Scientific Reports43:56 VueCore: Visualizing OMIX Data47:50 Using AI and LLMs in Bioinformatics50:25 R vs Python in Bioinformatics Tools53:17 Closing Thoughts from EcuadorConnect with SebastianTwitter - https://twitter.com/sayalaruanoLinkedin - https://linkedin.com/in/sayalaruano Github - https://github.com/sayalaruanoWebsite - https://sayalaruano.github.io/Connect with DataTalks.Club:Join the community - https://datatalks.club/slack.htmlSubscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQCheck other upcoming events - https://lu.ma/dtc-eventsGitHub: https://github.com/DataTalksClubLinkedIn - https://www.linkedin.com/company/datatalks-club/Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

Aishwarya Jadhav, a machine learning engineer with roles at Waymo and Tesla, shares her fascinating journey from finance to AI. She discusses designing an AI guide dog for the visually impaired and contributing to malaria mapping in Africa. Aishwarya also dives into the challenges of deploying safe autonomous systems, the interplay between sensor technologies like LiDAR and cameras, and the significance of gesture recognition in traffic control. Plus, she offers insights on how to break into the self-driving AI industry.

Ranjitha Kulkarni, a machine learning and NLP engineer with experience from Microsoft and Dropbox, now leads efforts at NeuBird.ai to create LLM-driven AI products. She shares fascinating insights on building reliable AI systems in the age of generative AI, emphasizing the importance of context engineering and dynamic planning. Ranjitha also discusses the evolution of agent technology, the role of retrieval in their design, and the future potential of agent marketplaces. Her practical tips on evaluating AI agents and the challenges of ensuring reliability are invaluable.

Abouzar Abbaspour, a data engineer with a rich background in machine learning and recommendation systems, shares his unique career journey from software engineering in Iran to working at Tesla. He delves into crowd modeling at Efteling, revealing how data from rides influenced visitor flow solutions. His transition to Bol.com highlights innovative brand recommendations, including a fun 'Tinder for brands' prototype. He also discusses the impact of large language models on productivity and how practical inference is revolutionizing his work at Tesla.

Dashel Ruiz, a data and machine learning practitioner with a rich background in semiconductors and software engineering, shares his fascinating career journey. He discusses transitioning from hardware to data science, revealing how he utilized machine learning to enhance semiconductor production. Dashel emphasizes the importance of practical experience in data education and contrasts it with traditional university methods. He also delves into his creative projects, like developing predictive models and APIs, while highlighting the value of community support in learning.

Micheal Lanham, an AI innovator with 20 years of experience in diverse fields like fintech and game development, shares his remarkable journey. He delves into the evolution of AI, the impactful role of evolutionary algorithms, and practical applications of AI agents. Micheal discusses how generative AI is transforming gaming and offers insights on designing minimalistic agent workflows for efficiency. He also provides valuable career advice for aspiring AI engineers and emphasizes the importance of continuous learning in a rapidly evolving tech landscape.