Doximity’s Post

Over my career I've thought a lot about "where should a data scientist sit in an org?" 👇 5 lessons from what I've learned after working in 6 very different companies. 1. DS under an MBA: maybe okay, probably bound for failure. 2. DS under the PM: def bound for failure. 3. DS under the DS: good for the junior in the short term. 4. DS under Eng: good. 5. DS under a people manager, but works closely integrated team with a DS-experienced tech lead: best. Interdisciplinary teams do the best work. It maximizes labor efficiency to have engineers, PMs, and DS's working on the same problem but doing different things. When you federate DS, they don't care as much about what they're working on. The incentives are off. When a DS works for a PM the PM will make wild assumptions about what they should do. PMs oversimplify problems and DS find that unsatisfying. DS reporting to DS means you throw stuff over the fence and the Eng do the real work. And the Eng don't capture all the nuance the DS would like to implement. DS reporting to business types is unfulfilling because DS love technical stuff. best scenario? Have a DS work in a pod with experienced tech leads. DS reports (HR purposes) to someone outside of the team who can give them guidance but is incapable of micromanaging them.

In today's #DATA-driven world, having a talented data specialists team is not just a "nice-to-have"—it's essential for business growth and innovation. 🚀 Hiring the best data engineers/analysts/architects/scientists can be a game-changer 💰 for any organization. Here’s why finding top talent in data is critical for any organization today: *#Transform Data into #Strategy: don’t just analyze data! Turn it into clear, actionable insights that guide decision-making across the organization *Streamline Processes & Drive #Efficiency: by implementing automation and improving data management, skilled data professionals save teams time and cut costs 💵 —allowing everyone to focus on high-value tasks *Drive #Innovation with Informed Decisions: good data specialists can spot trends early, opening doors to new products, tailored customer experiences, and growth in untapped markets 🌏 *Stay Competitive in a #Data-Driven World : as industries increasingly rely on data, having strong data talent positions your business, lead ⭐ rather than follow I you are looking for the best talents in #DATAEngineering, #DataAnalytics, #DataArchitecture, #DataScience for your business in the #DACH region or in #Poland, get in touch with me today! We have both, the necessary technical knowledge and access to the 💫 best candidates in the industry. Paulina.Suder@psdgroup.com +49 69 138 136 01 #DataSpecialists #DataDrivenSuccess #HiringTalent #BusinessGrowth #FutureReady #Innovation #Digitaltransformation #ITrecruitment #techtalent

😁 Good news! Hiring for Data Governance and Data Management is on the up! No surprise, how can businesses ride the AI wave without good quality, usable, secure data. But - 😣 Bad news... I still speak to too many Data Governance professionals who struggle to articulate the benefit they've provided to their prior employers. I don't think this means that they're not capable, but surely the best way to demonstrate your capability of taking your stakeholders on a journey, is to take your prospective employer on that journey too, in an interview scenario? ⚡ So my advice to anyone looking for their next data governance role - it's your time to shine, but go prepared into discussions with recruiters and hiring managers with notes about tangible benefits you've provided, and a strong awareness of your achievements, as well as the challenges you faced along the way. #datagovernance #datamanagement #datagovernancejobs #datagovernancecareers #ai

🔍 Why Outsource Data Science? Discover the Benefits! 🔍 In today’s data-driven world, harnessing the power of data science is essential for making informed decisions and driving innovation. But why should you consider outsourcing your data science needs? Here’s why: Access to Expertise: Outsourcing connects you with top-tier data scientists who have specialized skills and experience. They bring advanced knowledge and innovative solutions to tackle your data challenges. 💡 Cost Efficiency: Hiring a full-time, in-house data science team can be expensive. Outsourcing allows you to leverage high-quality expertise without the overhead costs of permanent staff. 💰 Scalability: Outsourcing offers flexibility to scale your data science capabilities up or down based on project needs. This adaptability ensures you get the support you need, exactly when you need it. 📈 Focus on Core Business: By outsourcing, you can focus on your core business activities while experts handle complex data analyses and insights. This leads to better efficiency and productivity across your organization. 🚀 Cutting-Edge Technology: External data science teams are often equipped with the latest tools and technologies. Stay ahead of the curve with access to the most advanced resources and methodologies. ⚙ At Techbridge Latam, we provide top-notch data science talent to help you unlock the full potential of your data. Ready to elevate your data strategy? Let’s connect! 🌐 💬 Reach out to us to explore how we can support your data science needs: www.techbridgelatam.com ... #DataScience #Outsourcing #TechbridgeLatam #BusinessIntelligence #CostEfficiency #Expertise #Innovation #DataStrategy #hr #techrecruitment #informationtechnologyjobs #itrecruitment #techhiring #itjobs #techtalent #techcareer #techhiringnow

🚀 𝗧𝗵𝗲 𝗦𝗲𝗰𝗿𝗲𝘁 𝗦𝗮𝘂𝗰𝗲 𝗳𝗼𝗿 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗛𝗶𝗴𝗵-𝗜𝗺𝗽𝗮𝗰𝘁 𝗗𝗮𝘁𝗮 𝗧𝗲𝗮𝗺 🚀 I've received multiple inquiries about how to build a successful data team after my recent post, so let’s break it down! 🛠️ 🔑 𝗪𝗵𝗮𝘁 𝗗𝗲𝗳𝗶𝗻𝗲𝘀 𝗦𝘂𝗰𝗰𝗲𝘀𝘀?   Success is when your data team empowers your company to make the right decisions and build impactful data products. For a Series A/B Scale-up, success means hiring 6-8 people in under 6 months. Here’s how to do it: 𝟭. 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗬𝗼𝘂𝗿 𝗣𝗿𝗼𝗳𝗶𝗹𝗲𝘀 🔍   Avoid unrealistic job descriptions asking for everything. A Data Engineer won’t master Analytics, and a Business Analyst won't excel in Machine Learning. Create a multidisciplinary team with specific, complementary expertise. Minimum, 3-5 specialists plus a manager. 𝟮. 𝗛𝗮𝘃𝗲 𝗮 𝗖𝗹𝗲𝗮𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 🎯   What does "good" look like for your data team? Candidates want to see that you have a vision and a target organization in mind. Clear expectations attract top talent. 𝟯. 𝗕𝗲 𝗙𝗹𝗲𝘅𝗶𝗯𝗹𝗲: 𝗥𝗲𝘃𝗲𝗿𝘀𝗲 𝗛𝗶𝗿𝗲 🔄   I've coined the term "Reverse Hire" to advocate for an open hiring strategy. Don’t pigeonhole yourself with rigid job specs. Find the best talent and then craft positions that excite them. Reassess your organization with each hire. 𝟰. 𝗩𝗮𝗹𝘂𝗲 𝗖𝘂𝗹𝘁𝘂𝗿𝗲 & 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 🌟   Prioritize cultural traits over specific skills. Successful team members are outcome-driven, and focused on business impact over technical excitement. Beware of tech enthusiasts without a business mindset. Prioritise the ones who "have done it before". 𝟱. 𝗖𝗼𝗻𝘀𝗶𝗱𝗲𝗿 𝗬𝗼𝘂𝗿 𝗦𝘁𝗮𝗴𝗲 🏢   Tailor your hiring to your company's stage. Do you need Machine Learning experts now, or should you first build a solid data foundation? -- 👇 𝗦𝗵𝗮𝗿𝗲 𝘆𝗼𝘂𝗿 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗶𝗻 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗱𝗮𝘁𝗮 𝘁𝗲𝗮𝗺, 𝗮𝗻𝗱 𝗹𝗲𝘁'𝘀 𝗰𝗼𝗻𝗻𝗲𝗰𝘁! With 20 years of experience in the data space and six successful scale-up cycles behind me (including Typeform, Preply, and MoonPay among others) I can help you build a high-impact data team, infrastructure, and processes. Reach out for expert advice today and avoid common pitfalls you’ll regret tomorrow. I'm available for consultancy and fractional/full-time VP roles. 📈 #DataLeadership #Fractional #VPofData #DataStrategy #ScaleUpSuccess #TechConsulting #ScaleUp #TechHiring #Leadership #DataTeam #TeamBuilding #SeriesA #SeriesB

WHO ARE YOU? You are likely a Head of Data & Analytics, or Chief Data Officer, with 7+ years’ experience crafting, developing, and deploying data solutions – a true practitioner. In this vein, we expect you to have failed. And to have seen the good, the bad, and the ugly of data science – and to have created a few monsters yourself! After all, data science is a craft. But, you’ve learnt by experience. Honing your skills. Creating efficiencies. Collaborating and learning from others. All with a view to striking a balance between what is practical today, versus, what might be needed tomorrow. You will use these years of experience to deliver commercial solutions, and practical insights that enable our clients to unlock the economic value of data in the short and medium term. This will be achieved through your ability to engage and hold senior-level conversations, write compelling reports, and craft recommendations – all of which are underpinned with best practice, well-constructed investment plans, and years of pattern recognition. DOES THIS SOUND LIKE YOU? https://lnkd.in/eBcusGkR

Current hiring trends across UK & Europe 👇👇👇 The role of CDO is becoming less clear ...❓❓ 💡Teams have shrunk and fragmented and there is a trend to migrate engineering into the CTO. There has been an uptick in offshoring data functions, which is in part down to cost management, but also the evolution and decentralisation of the data team. 💡I have also seen a large portion of the senior market moving into independent advisory roles, supporting SLT’s and c-suite in evaluating their current data capabilities, and whether they’re fit for purpose moving forward. 💡AI adoption has instilled paralysis within a number of leadership teams, so the role of Directors and Managers in this space has shifted. It reminds me of Covid, where organisations had to pivot at lightning speed, with little to no foresight of what the future might hold. Data Engineering ⛏️ 💡We’re seeing the opportunity for value creation appearing much earlier on in the data life cycle; where CTO’s were once wholly focused on cost, the shift to thinking about engineering as a value driver is occurring. Right now, businesses need to see improved returns from their data investments, and the focus is on instilling processes around quality, privacy and security earlier on in the process, building better tooling and automation for Engineers to ensure fewer mistakes, rather than relying on a separate governance or person or process at a later stage. 💡Over the last 20 years the role of the Analyst and in turn Data Scientist, has been to deliver significant commercial results through ad hoc projects, but they’ve struggled to build repeatable scalable solutions, and they need Data Engineers to turn the data into something robust and reliable. #hiringtrends #indsutryinsights #marketinsights

💡 Why Data Engineers Are the Backbone of Innovation in 2024 💡 In today’s data-driven world, Data Engineers are playing a pivotal role in shaping the future of business. Here’s why these unsung heroes are powering the innovation engine: Data is the New Gold 💰 Companies are collecting more data than ever, but without skilled data engineers to process, clean, and structure that data, it’s just noise. These experts turn raw data into actionable insights that fuel decision-making. Supporting AI & Machine Learning 🤖 AI and machine learning models rely heavily on quality data. Data engineers build the infrastructure that allows data scientists to develop cutting-edge algorithms and predictive models. Scalability & Efficiency ⚙️ From cloud platforms to big data solutions, data engineers ensure that companies can handle growing datasets efficiently, helping businesses scale faster and more cost-effectively. Driving Real-Time Analytics 📊 In fast-moving industries, real-time insights can be a game-changer. Data engineers create pipelines that make real-time data available, empowering companies to make instant, informed decisions. Enabling Personalization 🎯 Whether it’s personalized customer experiences or targeted marketing strategies, the work of data engineers is crucial for delivering tailored solutions that meet unique user needs. 🔑 Hiring Tip for 2024: As businesses increasingly rely on data-driven innovation, the demand for skilled data engineers is on the rise. If you're looking to stay ahead of the curve, building a strong data team should be a priority. Need help finding top data engineers? Let’s connect! I specialize in tech recruitment and can help you source the right talent to drive your business forward. #DataEngineering #TechHiring #Innovation #AI #MachineLearning #BigData #Recruitment

Efficiency with insightful data strategy is Key in today's tech landscape. As an IT recruiter, I've witnessed firsthand the pivotal role Data Architects play in transforming tech departments. They streamline data infrastructures, leading to: ✔️ Enhanced data clarity, empowering technical teams to devise precise, innovative solutions. ✔️ Seamless big data analytics, enabling scalable and forward-thinking projects. ✔️ Robust data security measures, safeguarding your company's invaluable digital assets. Ready to elevate your team with a Data Architect? Let's find the perfect talent to sculpt your data strategy. 💡 #ITRecruitment #DataArchitects #TechTalent

Tim manages a #retail company that is gearing up to launch a major new data analytics project. The problem? The data #engineering team is swamped, and hiring full-time staff takes too long and costs too much. Sarah, the head of data engineering, is exhausted. “We need more hands on deck,” she says. Tim realises that hiring full-time staff isn’t feasible right now. Tim turns to staff augmentation. Within a week, Tim brings on 3 experienced #data engineers—Alex, Priya, and Diego—through a reputable firm. They start immediately and integrate seamlessly with his team. The augmented engineers handle the heavy lifting of the project. Tim's in-house team can now focus on their regular tasks without burning out. The project progresses rapidly and meets every milestone. The new #analytics platform launches successfully, providing deep insights into customer behaviour, optimising inventory, and predicting trends. Tim's competitors are left wondering how he did it so fast.. You can be like Tim too. When internal resources are saturated, source for external experts. 🌟 #staffaugmentation #customerinsights #dataengineering