𝑻𝒊𝒑𝒔 𝒇𝒐𝒓 𝒏𝒆𝒘 𝑫𝒂𝒕𝒂 𝑺𝒄𝒊𝒆𝒏𝒄𝒆 𝑴𝒂𝒏𝒂𝒈𝒆𝒓𝒔 I became a manager in data science early in my career. It has been a journey fraught with failures and some successes. Here are some of my learnings along the way - 📈 𝑹𝒐𝒍𝒆, 𝒓𝒆𝒔𝒑𝒐𝒏𝒔𝒊𝒃𝒊𝒍𝒊𝒕𝒚 𝒂𝒏𝒅 𝒑𝒓𝒊𝒐𝒓𝒊𝒕𝒊𝒆𝒔 Early on, my vision was small which narrowed the value I was able to create. I had two focuses - 1) ship out high quality work, 2) coach & promote my team. After >10 years in leadership roles, here is how I NOW think of the responsibilities of a data science manager in the hierarchy of importance - 🔹 Build authentic relationships with stakeholders and team members 🔹 Identify and align on highest impact work the team can enable and unlock 🔹 Set up systems, processes, and people to execute on these projects 🔹 Manage projects and priorities 🔹 Coach your direct reports on execution Depending on the seniority of the role, the distribution across these may vary but the core buckets remain the same. 🏆 𝑩𝒆 𝒊𝒏 𝒕𝒉𝒆 𝑨𝒓𝒆𝒏𝒂 Don’t be carried away by the business of meetings that make you feel important but don’t create real value. Spend at least 1/3rd of your time towards hands-on work. Don’t get rusty on the technical chops. Be an SME in several areas in the workflow - tech stack/tools, data models, methodologies, algorithms and specific tables. This will build trust with your reports while reducing dependency, increasing team efficiency and productivity. 🔄 𝑻𝒂𝒊𝒍𝒐𝒓 𝑷𝒓𝒐𝒄𝒆𝒔𝒔𝒆𝒔 & 𝑷𝒓𝒐𝒅𝒖𝒄𝒕𝒔 Data science lacks standard processes, unlike software engineering, due to its evolving role, inherent variability in methods depending on project goals. Creating processes and systems that will help with the ground reality of the ecosystem and culture at your company, is important. 🎲 𝑼𝒏𝒅𝒆𝒓-𝑷𝒓𝒐𝒎𝒊𝒔𝒆 𝒂𝒏𝒅 𝑶𝒗𝒆𝒓-𝑫𝒆𝒍𝒊𝒗𝒆𝒓 In the unpredictable world of predictive modeling 😉, where factors such as data anomalies, algorithm biases, and unexpected market shifts can disrupt the accuracy of forecasts, it pays to temper expectations and try to exceed them. #datascience #analytics #businessanalytics #leadership #techleadership #careers #techmanagers
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🚀 Career Advancement Alert In today’s data-centric world, the ability to communicate data effectively is a must-have skill. With Data Visualization & Storytelling (DVST), you’ll become the go-to person in your organization for making data understandable, compelling, and action-driven. 🖋️ Who benefits from DVST? 1. Mid-level managers 2. Data scientists & analysts 3. Marketing & sales professionals 4. Finance experts 5. Strategic business leaders 🔍 What you’ll learn: 1. Craft a narrative around data that drives action. 2. Communicate complex information simply. 3. Turn insights into visual stories that lead to better business decisions. 🎓 Ready to stand out in your industry? Link to course in comments #CareerGrowth #DataSkills #DataVisualization #BusinessStorytelling #ProfessionalDevelopment #DVST
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I write about soft skills, communication, and career growth for data professionals. Learn how mastering communication and storytelling can be your high-impact, career-defining skill.
✨How to Refocus and Elevate Your Career as a Data Professional✨ Feeling stuck or disconnected in your data career? It’s easy to lose focus in a world of endless tasks, deadlines, and data reports that lack deeper meaning. Many of us go through the motions — the degree, the job — but what happens when the spark fades, and we feel like we’re just surviving? 📊It’s time to hit reset. In this post, I share insights on how to regain control, reignite your passion, and align your career with a greater purpose. By refocusing on personal growth, communication skills, leadership, and continuous learning, you can break free from stagnation and move forward with intention. 🔑 The first step? Acknowledge where you are, use frustration as fuel, and commit to rediscovering what truly matters to you. Let’s start this journey together. 🚀 Drop a comment below: What’s one thing you’d like to refocus on in your career? #DataProfessionals #CareerGrowth #SoftSkills #DataStorytelling #LeadershipInTech #CareerReset #ContinuousLearning #DataScience #SoftSkills #EffectiveCommunication #DataDrivenDecisions #Leadership #CareerGrowth #SoftSkillsForDataProfessionals #DataDrivenLeadership #StorytellingWithData #BusinessAnalytics #StakeholderEngagement #LeadershipDevelopment #DataVisualization #AnalyticsStrategy #DataScientists #TechnicalCommunication
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One thing I love about Analytics: there are doorways into so many other disciplines. I've known Analysts who went on to all kinds of cool fields: - Data science - Data engineering - Higher education - Financial analysis - People leadership - Analytics engineering - Product management - Operations management Personally I love analytics and plan to stay here for a long time. But you can take it in any direction! It teaches you a mix of technical skills, people skills, critical thinking and curiosity that are incredibly valuable. What path do you see yourself taking? #data #analytics #career #growth
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“The difference between successful people and really successful people is that really successful people say no to almost everything.” If you often find find yourself stuck on low-impact tasks that don’t drive results, you may not be protecting your time. A big parter of being a data scientist is juggling multiple stakeholders with multiple priorities. If we say "yes" to everything, it's very likely we won't end up doing the work that really moves the needle for the business, for our stakeholders, and for our own careers. But saying "no" can be really tough - it is often a delicate balance. I’ve learned over time that saying "no" is as much a skill as any technical expertise we develop as data scientists. Here are few ways to better protect your time when faced with competing priorities, so you can maintain focus on what truly matters: "That sounds interesting. Can you share how this aligns with our current top priorities?" → Helps evaluate whether the request is crucial to current goals. "Let’s talk about the effort required versus the potential impact." → Encourages stakeholders to weigh the return on investment for the effort involved. "We’re currently working on Project A to achieve Goal X. Does this request help move us closer to Goal X?" → This question redirects focus to the larger objective and helps reprioritize accordingly. "I’ll add this to the backlog and prioritize it against other tasks for this quarter. Let’s see where it fits." → Shows you're willing to consider the request but emphasizes that priority is given to more impactful tasks. "I’d love to help, but my current focus is on Project A. Can we revisit this next quarter?" → This defers the request without outright rejecting it, making room for a follow-up later. Curiosity is great, but balancing curiosity with business impact is even better. 👉 How do you politely say “no” to low-impact or "just curious" requests? Let me know in the comments! #productivity #timemanagement #stakeholdermanagement #prioritization #focus #leadership #datascience #decisionmaking
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Data Scientist at Sportsbet | Recommendation Systems | AI & Machine Learning | HealthTech Enthusiast | Data-Driven Insights
Technical skills are all it takes to succeed in Data Science. Think again. 5 non-technical skills every data scientist needs: 1️⃣ Stakeholder Whispering 🤝 - Turn raw data into actionable business insights. - Build trust faster than running a machine learning model. - Make executives not just hear but feel your impact. 2️⃣ Storytelling that Drives Action 📊 - Numbers don’t inspire decisions, but stories do. - Use visuals and narratives that stick. - Imagine your data telling a story that sparks, “Let’s act on this now.” 3️⃣ Collaboration Superpowers 🌟 - Be the bridge between technical and non-technical teams. - Break down silos and build stronger solutions. - A cohesive team is your secret weapon for success. 4️⃣ Business Intelligence 💡 - Think beyond the dataset—think strategy. - Align insights with business goals for maximum impact. - Speak the language of both data and decision-makers. 5️⃣ Communication Mastery 🗣️ - Simplify the complex and make it relatable. - Connect with every audience, from engineers to executives. - Insights delivered clearly = insights acted upon. 🔥 Technical skills might get you hired, but non-technical skills make you indispensable. Don’t let your potential get buried in code. Master these skills to transform yourself into a sought-after data science leader. What’s the #1 non-technical skill that’s helped you thrive in Data Science? #datascience #careergrowth #leadership #professionaldevelopment #techskills #collaboration #storytelling
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Project Manager | Business Analyst 3 years of experience | CRM | Accountant and Sales manager | Bachelor of Economics
Hey LinkedIn! I'm on the lookout for new adventures in the IT world and ready to take on the challenges of business analysis. My experience in IT has turned me into a requirements analysis and project management ninja, and my skills in data visualization and strategic planning have helped companies level up. I'm inspired by projects involving big data, machine learning, and product development. I want to help create innovations that drive business forward and upward. If you've got something exciting or know someone who can assist in my search, I'd love to connect and hear about opportunities. Thanks for stopping by! #BusinessAnalysis #IT #Data #MachineLearning #JobSearch
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Leadership | GCC | Retail | Technology, Engineering & Product | Data & Analytics | Architecture, Products & Platforms | Data-ops & Dev-ops | Strategy & Road-map | Digital Transformation
Priority Pandemonium: Taming the Chaos Leading a team amidst diverse priorities? Welcome to the ultimate juggling act! The Complexity Multiple teams, diverse priorities: - Data Analytics: data engineers (pipelines), data scientists (model accuracy), business analysts (insights) - Product Teams: roadmap, feature adoption, conversion rates - Business Teams: sales (revenue growth), marketing (brand awareness), finance (cost optimization) Too Many Cooks, Too Many Recipes Conflicting priorities, overlapping deadlines, and competing resources. It's like trying to solve a Rubik's Cube blindfolded! The Solution 1. Clear communication (no more telepathy) 2. Cross-functional workshops (coffee-fueled collaboration) 3. Unified priority framework (one list to rule them all) 4. Regular alignment sessions (stay on track) 5. Adaptive planning (pivot, don't panic) Tame the Chaos Establish a shared understanding, prioritize collectively, and drive progress. #Leadership #Prioritization #TeamAlignment #Complexity #DataAnalytics #Product #Business
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🌟 To all future @Data Analysts, Scientists, Software Engineers, and Project Managers—this one’s for you! 🌟 We’re all on the journey together, and I want to remind you: 🔥 You’ve got what it takes! Whether you’re learning to code, analyze data, or manage projects, every step you take brings you closer to your dream. Here’s what I’ve learned: 1️⃣ Stay curious — Curiosity drives innovation. Keep asking questions and digging deeper. 2️⃣ Embrace failure — Every mistake is a lesson. It's a step forward, not a setback. 3️⃣ Consistency is key — Small efforts each day add up to BIG results. 4️⃣ Never stop learning — The tech world is always evolving. Keep growing, keep adapting. 🚀 ✨ Remember, your path to success is unique, and with hard work, anything is possible. If I can do it, so can you. Let’s support each other on this journey to becoming the next wave of Data Scientists, Analysts, Engineers, and Project Managers. 💡 Ready to connect? Let’s learn, share, and grow together! #MotivationMonday #DataScience #DataAnalytics #SoftwareEngineering #ProjectManagement #TechCommunity #LearningJourney #CareerGrowth #FutureLeaders #Students #KeepGrowing
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Impressive insights here. To further innovate, consider implementing multi-variant testing strategies beyond the traditional A/B testing to optimize all aspects of project management and execution for unprecedented efficiency.