Beyond Resume

Everyone talks about tools.Few talk about decisions.In this episode of Beyond Resume, Sourabh Girdhar (ex-CTO, care.fi & Gartner Engineering Ambassador) shares what really drives success in modern engineering.We explore:• The shift from individual contributor to leadership• Why “false maturity” exists in DevOps and agile teams• How AI can amplify broken systems• The importance of ownership and decision velocity• Why engineering is more about people than codeIf you’re building systems, teams, or a long-term career in tech — this episode will challenge how you think.#Engineering #Leadership #AI #DevOps #BeyondResume

Everyone wants to predict the next AI breakthrough.But what actually stays?In this segment from Beyond Resume, Suvadip shares a grounded perspective on the future of analytics — why tools and techniques will keep evolving, but problem solving will remain the core skill.We discuss:• Why predicting the “next big thing” is overrated• Why tools are just tools• Why upgrading your thinking matters more than upgrading software• What will stay relevant over the next decadeIf you're building a long-term career in analytics, this perspective matters.#AI #DataScience #FutureOfWork #Analytics #Leadership

Most data leaders write whitepapers.Suvadip writes fiction.In this segment, we explore:• Why he started writing data science fiction• How satire fits into the analytics world• The creative side of data professionals• Why stories matter as much as modelsAnd yes — there’s a hint about his third book.If you think analytics is only about code and dashboards, this conversation might surprise you.#DataScience #AI #Fiction #Leadership #BeyondResume

Retail banking analytics and commercial banking analytics may sound similar.They are not.In this segment from Beyond Resume, Suvadip Chakraborty breaks down the real differences between retail and commercial banking analytics — from product complexity to relationship-driven decision making.We discuss:• Why commercial banking products are structurally different• The role of relationship managers in decision making• Why models don’t make final decisions in commercial banking• The impact of geopolitics and regulation• Why commercial analytics is more network-driven and context-heavyIf you’ve worked in retail analytics and are curious about commercial banking — this segment gives you clarity.#Analytics #Banking #DataScience #Leadership #BeyondResume

What does a long, evolving career in analytics actually look like?In this episode of Beyond Resume, I speak with Suvadip Chakraborty — Associate Director & Head of Global Analytics — about building depth, relevance, and creative satisfaction over 17 years in the same organization.This is not a conversation about tools.It’s about craft.We discuss:• Moving from economics to analytics by accident• Staying in one organization without staying stagnant• Building a new analytics vertical from scratch• Retail vs commercial banking analytics• Why tools evolve — but problem solving stays• Writing data science fiction• And a small surprise for his readersIf you're early in your career — or 15 years in and wondering what long-term growth looks like — this episode will resonate.Your career is more than what’s on your resume.#Analytics #AI #Leadership #DataScience #CareerGrowth

Leadership in analytics isn’t just about delivery metrics.In this segment, Anirban Nandi explains why trust, empathy, and long-term people investment are the foundation of high-performing AI teams.We discuss:• Creating psychological safety• Developing talent deliberately• Ethical responsibility in analytics• Sustained performance vs short-term winsIf you're building teams, this one is powerful.

How do you build a Data Lab from zero?In this focused segment from Beyond Resume, Anirban Nandi shares his experience building analytics capabilities from scratch across multiple organizations.We explore:• The first 90-day decisions that matter• How to prioritize early use cases• The importance of stakeholder buy-in• Funding strategy for AI initiatives• Creating a culture of ownership and curiosityIf you're setting up an AI or analytics team, this conversation will give you a practical blueprint.

What does it mean to lead both upward and downward?In this segment from Beyond Resume, Anirban Nandi shares practical insights into managing executive expectations while building high-performing analytics teams.You’ll learn:• How to align with senior leadership• How to shield and empower your team• Why communication is the hidden lever of analytics successA must-watch for analytics managers and emerging leaders.

What does it take to build AI and Data capabilities from zero?In this episode of Beyond Resume, Kausik Kumar sits down with Anirban Nandi, Vice President – AI & Data at Albertsons Companies India, to unpack 18 years of building analytics functions from the ground up.From his early years at Target to establishing Data Labs at Landmark Group and Rakuten India, Anirban shares hard-earned lessons on leadership, ethics, talent development, and scaling analytics across geographies.In this episode, we discuss:• The Target analytics culture and long-term learning mindset• The ethical responsibility of predictive analytics• How to go from zero to a functioning Data Lab• Early wins that build trust and funding• Why analytics is fundamentally a change management problem• Leadership: trust, empathy, and investing in people• Depth vs breadth in career growthSound Bites:“Build people before you build outcomes.”“Talent is universal. Context is not.”“Data beating the gut feel is powerful.”If you are:– Building AI teams– Leading analytics functions– Early in your data career– Or navigating leadership growthThis episode is for you.#AI #Analytics #Leadership #DataScience #CareerGrowth

From Bengali Medium to BI Expert: How Ankita Das Overcame Language & Coding BarriersAnkita Das didn't start with the "typical" background for a data professional.She came from Bengali medium schooling and felt nervous speaking English. She had no coding background when she decided to enter analytics.In this clip from Beyond Resume, Ankita shares her practical approach to overcoming these barriers—and the powerful framework she discovered: consistency + compounding = confidence.

"BI is About Insights, Not Charts" - Ankita Das on What Really Matters in Data VisualizationMost people focus on making dashboards look good. Ankita Das focuses on making them meaningful.In this clip from Beyond Resume, Ankita explains why the real foundation of Business Intelligence isn't chart aesthetics—it's the backend data modeling that makes insights possible.

"Mistakes Boost My Confidence" - How Ankita Das Transformed Her Relationship with FailureAnkita Das, Business Intelligence Expert, used to be afraid of challenges and mistakes. Today, she embraces them as her primary learning tool.In this clip from Beyond Resume, Ankita shares the mindset shift that changed her career trajectory.🎯 WHAT ANKITA SHARES:- Why she was initially afraid to face challenges and make mistakes- The realization that all real learning comes from resolving mistakes- How mistakes build confidence and lead to taking ownership- The shift from fear-based thinking to curiosity-based problem-solving💡 KEY QUOTE:"Whenever I learn something new, it comes from mistakes—and resolving those mistakes boosts my confidence. That confidence led me to explore more, take ownership of my work, and now I approach every problem with a mindset of curiosity instead of fear."🎙️ FULL EPISODE: [Link to full episode]📌 ABOUT ANKITA DAS:Ankita is a Business Intelligence Expert specializing in Power BI and Tableau, helping organizations transform data into actionable insights.📌 ABOUT BEYOND RESUME:Where careers and analytics come alive. Host Kausik Kumar explores the intersection of innovation and human experience with leaders and rising talents in analytics and AI.🔔 SUBSCRIBE for more insights from analytics and AI professionals.#GrowthMindset #BusinessIntelligence #CareerGrowth #Mistakes #Learning #BeyondResume #DataScience

FROM ECONOMICS TO BI EXPERT: Ankita Das on Overcoming Barriers & Building Strong FoundationsAnkita Das didn't start with a coding background. She came from a Bengali medium education and felt nervous speaking English. She was preparing for government jobs that didn't align with her interests.But she made a choice: Follow her passion for data, numbers, and creating real-world impact.In this Beyond Resume conversation, Ankita shares her journey from Economics graduate to Business Intelligence expert—and the lessons she learned along the way.🎯 WHAT WE DISCUSS:→ The moment Ankita realized government jobs weren't her path (00:00)→ How she discovered analytics and data science in 2020 (03:15)→ Overcoming language barriers and lack of coding knowledge (08:30)→ The power of consistency and compounding in skill development (12:45)→ Why data modeling is more important than dashboard aesthetics (18:20)→ Walking away from MNC offers that didn't match her interests (24:10)→ The real purpose of BI: Insights, not just charts (28:45)→ How remote work shaped her collaboration approach (32:00)💡 KEY TAKEAWAYS:- "Most people think BI is about making charts. It's not. It's about revealing insights that drive decisions."- "Whenever I learn something new, it comes from mistakes—and resolving those mistakes boosts my confidence."- "Doing things where your interests don't match is scarier than anything."- "A good dashboard always starts with a good backend."🎙️ ABOUT BEYOND RESUME:Beyond Resume explores the intersection of innovation and human experience in analytics and AI. Host Kausik Kumar sits down with leaders, rising talents, and change-makers to uncover the stories behind the resumes.📌 CONNECT WITH ANKITA DAS:LinkedIn: https://www.linkedin.com/in/ankita-das-7339aa123/📌 CONNECT WITH KAUSIK KUMAR:LinkedIn: https://www.linkedin.com/in/kausik-kumar-a2b5774/🔔 SUBSCRIBE for more conversations with analytics and AI leaders shaping the future of data.#BusinessIntelligence #DataVisualization #PowerBI #Tableau #CareerGrowth #Analytics #DataScience #BeyondResume #DataModeling #BIExpert

"At a time when we're hearing lots of negativity, reading Factfulness and being reminded to think rationally and look at the facts was like a breath of fresh air."Lindsay Pellow on the book that challenged her biases - even after 25 years in data science.Factfulness by Hans Rosling starts with a quiz about global trends. Lindsay got a low score. Most people do.The data shows:- Lower percentage living in poverty now vs. 30-40 years ago- Higher percentage of girls completing school- Deaths from natural disasters less than half what they were 100 years agoThe gap between what we believe and what the data shows is massive.Lindsay's insight: Even data professionals have biases that blind them to facts. "You learn about your own biases first, and I got a pretty low score."The reminder: Return to what we're supposed to be good at - looking at actual data, not our feelings about data.In a world of overwhelming negativity, Factfulness is evidence-based hope. Not wishful thinking. Measurable progress.The world has problems. But we're solving them faster than we think.From Beyond Resume with Kausik Kumar.

"A few years ago data was finally front and centre. Now developers are the group everyone wants. But we need both, working together, to develop better products."Lindsay Pellow on why data vs. tech competition misses the point.The problem she saw: Tech team building a platform that could count "how many customers did thing X" but not identify WHICH customers. Result? Can't understand how high-value customers use the product. Flying blind on whether tech drives value.The solution she implemented: Data team working alongside tech team from day one. Data professionals involved in choosing solutions, measuring impact, planning future value. Both teams learning from each other.Result: Smoother implementation. Better product.Lindsay's witnessed 25 years of evolution: from physical catalogues and call centres to the UK's biggest online retailer. Customer experience is now driven by technology - but only businesses using data to inform and understand that technology are truly succeeding.The trend: First data science was hot. Now developers are. The mistake: thinking it's either/or. The reality: we need both.From Beyond Resume with Kausik Kumar.

"I only knew operational research from a test they gave me. But that test captured my interest - using maths to solve real problems."Lindsay Pellow on how a borrowed typewriter, her mum's timing, and a single test launched a 25-year data science career.She wanted to be a doctor. Didn't get the grades. Twice. Studied maths instead. Had no idea what to do after university.Then her mum, who worked in a call centre, spotted a job ad on the notice board - for an "operational research analyst." The closing date? That Friday. Lindsay asked if she could deliver her application over the weekend. They said yes.She typed a CV on a borrowed electronic typewriter (no computer at home), posted it through the door on Sunday. The format actually made it stand out.She still didn't know what operational research was. But they gave her a test: use data to solve fraud detection. The test captured her interest - the idea of using maths to solve real business problems.When asked in the interview "what does operational research mean to you," she could answer - because of that test.She got the job. The rest is history. 25 years later, she's one of the most loved leaders in data science.The lesson: The best careers often begin accidentally. Not with perfect plans, but with curiosity meeting opportunity.From Beyond Resume with Kausik Kumar.

"Put simply, be the leader you want to have."Lindsay Pellow on what makes someone a loved leader in data science - not just respected, but genuinely loved.Lindsay and I worked together at HSBC over a decade ago. She was one of the most loved leaders I've encountered. This conversation explores why, through 25 years of lessons in human-centered data science leadership.KEY TOPICS:- The accidental start: How a borrowed typewriter and her mum's timing launched a 25-year career- The Co-op lesson: Getting humbled when she focused on outcomes instead of understanding people's workload and priorities- Enabling teams: Why telling people what to do is boring and how to embrace their ideas instead- Adapting leadership style: Different 1-2-1 formats for different personalities- Data + Tech partnerships: Why both need to work together, not compete- Beyond revenue: Using data to measure social impact at a photography gallery- Building relationships: The most important skill in data scienceMEMORABLE MOMENTS:→ "Several times my team members were saying 'but who's going to do the analysis?' and I was saying 'I can still code, you know!'"→ "1-2-1s belong to the individual, not the manager"→ "Anyone who is contributing is welcome - I don't believe in hierarchy"→ "When team members technically surpass you and take over stakeholder relationships, that's a win-win"→ "Be the gatekeeper when needed - your team needs to know you have their back"Lindsay's leadership philosophy isn't about grand vision speeches. It's about small, consistent choices: adapting to personalities, clearing obstacles, enabling growth, being transparent about strategy, and understanding that everyone works differently.Her career spans retail, financial services, affiliate marketing, and now the not-for-profit sector serving on a photography gallery board. She's seen data science evolve from mainframe printouts to real-time AI. But what hasn't changed: the importance of putting people first.If you're leading a team, building one, or wondering what human-centered leadership actually looks like in data science - this episode is for you.From Beyond Resume with Kausik Kumar - where careers and analytics come alive.Full episode available on all platforms.

Sanmita Sengupta shares one of the most vulnerable moments of her career: blabbering incoherently in a high-stakes regulatory meeting with significant RWA release on the line.A simple technical question. No preparation. An incoherent answer. Coming out of the meeting "red-faced" with her manager's "choice words" ringing in her ears.But here's what matters: what she did next. Acknowledged the mistake openly. Started remediation within the hour. Prepared a one-slide comparison. Sent it over quickly. Model approved in two weeks.Three lessons: Meticulous preparation matters. Accountability is everything. Regulators are willing to collaborate if you allow them to.The way you handle failure matters more than the failure itself.From Beyond Resume with Kausik Kumar.Full episode available on all podcast platforms.

Sanmita Sengupta traces the evolution of credit risk frameworks over two decades - showing how each major financial crisis fundamentally reshaped how banks assess risk.From Basel II's risk-based approach to the 2008 Global Financial Crisis that exposed backward-looking model failures, to IFRS 9's forward-looking expected credit loss framework, to Basel 3.1's push for consistency - every framework was written in the aftermath of disaster.Key insight: Credit risk professionals need to stay informed about regulatory thought process and emerging risks. The next evolution (climate risk, AI-ML transparency) is already here.Are we getting ahead of the next crisis, or waiting for it to write the next framework?From Beyond Resume with Kausik Kumar.Full episode available on all podcast platforms.

Sanmita Sengupta explains the fundamental challenge facing credit risk modeling today: incorporating climate risk when banks don't collect the data they need.A 30-year mortgage needs to consider if the property will go underwater in 20 years - but banks don't have flood risk data, sea level projections, or physical climate scores. Regulators are demanding transparency before the infrastructure exists.The solution? Partner with universities and climate research organizations for physical risk scores that can integrate into traditional credit models.Climate risk integration isn't optional anymore - it's reshaping how credit risk works.From Beyond Resume with Kausik Kumar.Full episode available on all podcast platforms.

"I only knew Basel as a city in Switzerland."That's how Sanmita Sengupta describes her entry into credit risk modeling - a field she'd accidentally stumble into and spend the next 20 years mastering.In this episode of Beyond Resume, I reconnect with my Statistics postgrad batchmate to explore what it really takes to build deep domain expertise in one of the most complex areas of financial services.Sanmita's journey spans India, Qatar, and Singapore. She's navigated PRA, MAS, and HKMA regulatory frameworks. She's built Basel II IRB models, designed IFRS 9 provisioning frameworks, and guided organizations through Basel 3.1 transitions.But what makes her story compelling isn't just the technical depth - it's the honesty, accountability, and intellectual humility she brings to the work.KEY TOPICS:- The unplanned pivot from Pharma Analytics to Basel II modeling- The regulatory meeting that went sideways—and the recovery that saved a massive RWA release- Why "perfect models" don't exist—and why admitting limitations builds trust- Emerging challenges: Climate Risk integration and AI-ML model transparency- Her philosophy: "Good credit risk modeling is about common sense and business discipline"- Working across cultures and regulatory regimes- The "buck-stops-here" attitude that powered her careerMEMORABLE MOMENTS:→ How meticulous preparation and owning mistakes turned a failed meeting into regulatory approval→ Why staying informed about regulatory thinking matters more than just compliance→ The challenge of incorporating 30-year climate projections into mortgage default models→ Why great working relationships don't require personal rapport→ The power of setting realistic expectations rather than oversellingSanmita represents something rare: deep specialization combined with intellectual humility. She admits when she doesn't know something. She sets realistic expectations. She values common sense as much as statistical rigor.This is for anyone building expertise in a technical domain, navigating regulatory complexity, or trying to understand what real mastery looks like beyond the resume.From Beyond Resume with Kausik Kumar - where careers and analytics come alive.

Phil Marquis breaks his own cardinal rule - building a model without business support - and turns it into his biggest win. The key? Deep business understanding and the ability to "paint a story with numbers" that executives could relate to.In 60 seconds, a skeptical division leader became his biggest advocate. Not because of statistical rigor, but because Phil translated technical insights into business value.The difference between models that die in boardrooms and models that get funded? Business translation skills.From Beyond Resume with Kausik Kumar.Full episode available on all podcast platforms.

Phil Marquis explains why servant leadership - prioritizing team needs over personal ambition - is the competitive advantage most leaders overlook. He shares a powerful example of putting team members in front of executives instead of taking credit, and how this built loyalty that couldn't be bought."A leader is only as successful as their team." When you empower others, you multiply your impact.From Beyond Resume with Kausik Kumar.Full episode available on all podcast platforms.

Phil Marquis addresses the fear many professionals face: AI displacement. His take? Worry won't keep you relevant—adaptability will. A quick 30-second reality check on what actually matters in the AI era.From Beyond Resume with Kausik Kumar.Full episode available on all podcast platforms.

Phil Marquis addresses the fear many professionals face: AI displacement. His take? Worry won't keep you relevant—adaptability will. A quick 30-second reality check on what actually matters in the AI era.From Beyond Resume with Kausik Kumar.Full episode available on all podcast platforms.

Phil Marquis, owner of Marquis Consulting Services with nearly 25 years of experience, shares his journey from analyst to leadership and reveals why soft skills matter as much as technical expertise in analytics.In this premiere episode of Beyond Resume, Phil discusses pivotal career moments, the importance of business context over pure technical ability, and how servant leadership has defined his approach to building analytics teams.🎯 KEY TOPICS COVERED:The Origin Story- Transitioning from individual contributor to analytics leader- The meaning of "balance" in technical teams- Building soft skills alongside technical expertiseThe Breakthrough Moment - Taking a calculated risk: building a model without business support- The 60-second moment that changed everything- Translating technical insights into business valueTechnical Evolution & AI- The shift from traditional modeling to machine learning- Why soft skills are the competitive advantage in the AI era- What to focus on when AI tools automate technical workLeadership Philosophy- Servant leadership: putting team needs over personal ambition- Building trust through people-first leadership- Developing team members and creating growth opportunities⏱️ TIMESTAMPS:00:00 - Welcome & Introduction02:00 - Phil's Origin Story08:00 - The Breakthrough Moment15:00 - Technical Insights: AI & ML23:00 - Leadership & Team Building29:00 - Lightning Round32:00 - Final Takeaway💼 ABOUT THE GUEST:Phil MarquisOwner, Marquis Consulting Services LLCNearly 25 years in analytics and AI leadershipFormer Fortune 500 analytics executiveSpecializes in: Business partner engagement, influencing executives, building advocacy, career development, and translating business needs to data science teams.🎙️ ABOUT THE HOST:Kausik KumarBuilding analytics teams and AI strategies that drive enterprise transformation for 20+ years🎬 ABOUT BEYOND RESUME:Beyond Resume explores the intersection of innovation and human experience through authentic conversations with analytics and AI leaders.Each 25-minute episode uncovers:- Real stories behind successful careers- Pivotal moments that defined leadership journeys - Technical insights from building analytics teams at scale- The human side of data science and AI leadershipPerfect for:- Data analysts starting their careers- Data scientists advancing into leadership- Analytics managers building teams- Anyone interested in AI/ML careers- Students exploring analytics paths