humanworks

At humanworks, we do b2b marketing differently. Bland, boring and blah blah blah B2B isn’t for us. We’re storytelling specialists, working with forward-thinking, growth-minded businesses to put the human connection at the heart of B2B marketing.

What we offer:

Content strategy
• Editorial
• Value proposition development
• Content audits

Brand awareness
• Thought leadership campaigns
• Industry reports
• SEO Blog articles

Lead generation
• E-books
• Whitepapers
• Email communications
• Paid ads

Social media
• Social media strategy
• Content creation and ghostwriting
• LinkedIn content
• Company page management

Communications & copy
• PR
• Website content & SEO
• Landing pages
• Case studies
• Employee engagement

Video & design
• Brand design
• Website design
• Video content
• Infographics

Founder

Cosmo Creative Content

If you're a b2b marketing director in financial services, insurance, SaaS and sustainability - we work with you to deliver the thought leadership strategy and content your in-house teams can't.

Content Director

BBC Radio 5 Live

-	Senior leader of the 5 live Breakfast programme and the wider 5 live network leadership team.
-	Leading a team of 20 producers creating a network breakfast radio programme 7 days a week. Responsibility for team performance and welfare.
-	Overseeing the on-air team, managing key talent and setting the editorial direction of the programme. 
-	Leading the commissioning of the programme’s digital and social content   

INNOVATION & LEADERSHIP

-	Leading the recent re-development of the 5 live Breakfast programme: creating a modern radio programme with the audience at its heart. Developing new formats and a programme clock to better showcase presenter talent – driving increased engagement and audience appreciation.
-	Leading 5 live Breakfast’s acclaimed Brexit coverage: developing formats like #BrexitBarometer (a simultaneous discussion format, on-air and online). Driving significant social media traffic.
-	Leading 5 Live Breakfast’s 2019 Election coverage, including creating record levels of engagement with the 5 Live Leader Your Calls, broadcast simultaneously on the BBC News Channel (the leaders of the main political parties taking listeners’ questions). Demonstrating an ability to lead high-profile projects with multiple stakeholders.

STRATEGIC HIGHLIGHTS:
-	Leading a 5 live strategy to improve our reach to younger audiences. Collaborating with multiple stake-holders and creating a blueprint that has had a real impact: 25-44 measure up on Rajars Q4 2019, significantly more live listening through BBC Sounds for U35s (Q3 vs Q4 2019)
-	Leading the BBC's 50:50 project to encourage greater diversity of voices on-air.
-	Currently leading on a project to develop a unique strategy to increase live listening through BBC Sounds (Q1 2020). Working across the BBC Radio division, engaging and managing multiple stakeholders. Demonstrating an ability to identify problems across the division and bring a team together to tackle them.

Assistant Editor

Senior Broadcast Journalist

Broadcast Journalist

THEN → BBC Journalist For 17 Years NOW → Building a B2B Content Agency HOW → Transforming Your Business Into a Thought Leader

At humanworks, we do b2b marketing differently. Bland, boring and blah blah blah B2B isn’t for us. We’re storytelling specialists, working with forward-thinking, growth-minded businesses to put the human connection at the heart of B2B marketing.

What we offer:

Content strategy
• Editorial
• Value proposition development
• Content audits

Brand awareness
• Thought leadership campaigns
• Industry reports
• SEO Blog articles

Lead generation
• E-books
• Whitepapers
• Email communications
• Paid ads

Social media
• Social media strategy
• Content creation and ghostwriting
• LinkedIn content
• Company page management

Communications & copy
• PR
• Website content & SEO
• Landing pages
• Case studies
• Employee engagement

Video & design
• Brand design
• Website design
• Video content
• Infographics

_________________________________

Why choose humanworks?

We don’t think business to business; we think human to human.

That means crafting content and communications that create genuine, personal, and authentic connections between your business and your customers.

We’re a new type of marketing agency. We help you cut through the blah, blah, blah and give your business a compelling story that will help you stand out from the crowd, build your brand, and grow your bottom line.

• We’re storytellers
• We’re thinkers & doers
• We’re humans, not robots

Our content doesn’t just click with your audience; it connects your business to new leads and converts them into customers.

That’s the power of human-to-human marketing. It just works.

__________________________

Our founder:

I’m Cosmo Shield, founder of humanworks. Before you ask, yes, that’s my real name! I was a BBC journalist for almost two decades before I realised I was sick of telling people bad news every day and wanted to help a generation of businesses tell their stories in a more compelling way.

That’s the passion the humanworks team brings to every client and project. I’d love to hear more about your business.

Email
cosmo@human-works.co.uk

Website:
www.human-works.co.uk

Cosmo Shield ♾

🤖Data Scientist | Turning Raw Data into Money Generating Insights | Data-led Growth for Your Business 🚀

Freelance Data Scientist | ML Engineer | SQL | Python | Power BI | MLOps

Data analytics and Machine learning models built 5X faster - no quality compromise. Worked with 14 clients in 7 different industries in the last 3 years. Helped current company scale to $5M+ ARR. Featured TOP RATED PLUS talent on Upwork in 2025 with 100% job completion and satisfaction.

My Toolkit:
- Data analytics: Python, SQL, Excel
- ML Engineering: FastAPI, AWS, Streamlit, great_expectations
- Data visualization: PowerPoint, PowerBI, Plotly, Matplotlib
- Data modeling: Scikit-learn, TensorFlow, Keras
- MLOPs: CI/CD (GitHub Actions), Docker
- Additional tools: Notion, n8n, Canva, Git/GitHub

My Stats:
- 5-stars reviews on 99% of projects delivered.
- 100% Job Success Score for on-time, budget delivery.
- Helped scale currently business to $5M ARR with ATS analysis & Reporting.
- 1.5 years TOP RATER PLUS on Upwork.
- 1800 hours billed.
- $60k+ earned.

What You’ll Get Working With Me:
- A data analyst who is a real problem solver.
- Quick responses (within the hour on working hours)
- Clean, maintainable code and detailed documentation
- A clear “NO” if something isn’t feasible; no wasted time
- A well-crafted report or dashboard as per the requirements

My clients think:
- "Anas is great and highly knowledgeable. He is passionate about solving data science challenges and has helped me significantly streamline some of my processes, enabling better scalability.
- "Anas, was prompt and thorough and I would def use him again in the future."
- "Anas is great to work with. He made the job so fluid and his knowledge of data science makes him someone worth listening to. I’m glad I chose him for my small business. I’m looking forward to what’s coming next, and I would definitely hire him again."

Popular Clients & Products:
- Uhubs: Financial company based in London
- AllAboutGroup: Law recruitment firm based in London
- Growth Dynamics: Marketing and data strategist based in London.
- Adway: Tech and recruitment company based in Gotheborg, Sweden

About me:
- Football fan since I can remember (Real Madrid fan)
- Tennis lover and practitioner (one-handed backhand style)
- Mangas fan (One Piece, Naruto, Bleach)
- Travel addict (South Asia, Europe, Africa, America (soon))
- Reading is something I enjoy as much as coffee (oat latte fan recently)

-----

YouTube Channel
→ GO HERE: https://www.youtube.com/anas_riad

Request services via LinkedIn or Email below:
r.riadanas@gmail.com

Hire on Upwork:
https://www.upwork.com/freelancers/~0163377bf3029c7553

Anas Riad

Not every problem needs an LLM. 
Some need 12 characters of regex.

I see people spending $𝟬.𝟬𝟯 𝗽𝗲𝗿 𝗔𝗣𝗜 𝗰𝗮𝗹𝗹 to extract emails from text.

Meanwhile: ⤵️

[𝗮-𝘇𝗔-𝗭𝟬-𝟵+_.-]+@[\𝘄-]+\.\𝘄+

Done. 𝗭𝗲𝗿𝗼 𝗰𝗼𝘀𝘁. Runs in milliseconds.

We're in 2026 and somehow we forgot that basic code still works. 

Not everything needs a prompt, a model, and a 3-second response time.

Need to validate a phone number? 
→ Regex. 

Need to clean whitespace from 10,000 rows? 
→ A one-liner. 

Need to rename 500 files? 
→ A bash script your laptop runs in 0.2 seconds.

LLMs are incredible for reasoning, writing, and ambiguity. 
But when the task has a clear rule and a predictable pattern, just write the rule.

Cheaper. Faster. More reliable.
Stop using a rocket ship to cross the street.

PS: Do you use LLMs for everything because it's convenient?

♻️ Repost if your network needs this reminder 
📌 Save it for the next time you almost open ChatGPT/Claude for string matching

Follow me for more → Anas Riad

Data Scientist & BI Consultant @Adway • ML Engineer • YouTube @ Anas Riad

Dear recruiters,

If you expect a Data Scientist to be an expert in:

→ Python for large-scale data analysis
→ Excel with complex financial-style reports
→ Pandas and NumPy on real, broken datasets
→ Heavy data cleaning and feature engineering
→ Git workflows, CI/CD, and automated testing
→ LLMs, prompt design, and applied AI use cases
→ Business KPIs, north-star metrics, and trade-offs
→ Clear storytelling with non-technical stakeholders
→ Dockerized environments and reproducible pipelines
→ Experiment tracking, model versioning, and rollbacks
→ Data pipelines touching cloud storage and warehouses
→ Regression, classification, and model selection at scale
→ Advanced SQL with messy joins and window functions
→ Exploratory analysis with Matplotlib, Plotly, and Seaborn
→ Probability theory, hypothesis testing, and A/B experiments
→ Bias–variance trade-offs and model performance monitoring

… you’re not hiring one 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁.
You’re describing an 𝗲𝗻𝘁𝗶𝗿𝗲 𝗱𝗮𝘁𝗮 𝗱𝗲𝗽𝗮𝗿𝘁𝗺𝗲𝗻𝘁.

PS: Post inspired by José Siles

📌 Follow Anas Riad for more content around data science

YouTube is still the BEST place to learn ML.

Most people still watch the wrong videos.

Here are 𝟭𝟮 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝘃𝗶𝗱𝗲𝗼𝘀 𝘁𝗼 𝗺𝗮𝘀𝘁𝗲𝗿 ML ⤵️ 

---

𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱 𝗖𝗦𝟮𝟮𝟵: 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴
 
The legendary starting point for ML.
Covers core theory, intuition, and key algorithms.

Video: https://lnkd.in/e-aJRQun
 
---

𝗔𝗹𝗹 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱 𝗶𝗻 𝟮𝟮 𝗠𝗶𝗻𝘂𝘁𝗲𝘀

A fast, structured overview of all major ML concepts.
Great for building a mental map before going deeper.
 
Video: https://lnkd.in/exCP58F6
 
---

𝗠𝗟𝗢𝗽𝘀 𝗖𝗼𝘂𝗿𝘀𝗲 𝗳𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀
 
Shows how ML actually works in real products.
Pipelines, deployment, monitoring, and production mindset.
 
Video: https://lnkd.in/erzM3b4F

---

𝗛𝗼𝘄 𝘁𝗼 𝗗𝗲𝗽𝗹𝗼𝘆 𝗠𝗟 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 (𝗙𝗮𝘀𝘁𝗔𝗣𝗜, 𝗗𝗼𝗰𝗸𝗲𝗿, 𝗔𝗪𝗦)
 
From trained model to live service.
A practical deployment walkthrough with modern tools.
 
Video: https://lnkd.in/e3JtcAZk

---

𝗦𝘁𝗲𝗮𝗹 𝗠𝘆 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗧𝗲𝗺𝗽𝗹𝗮𝘁𝗲

Learn how to structure ML projects properly.
Clean folders, reproducibility, and real-world practices.
 
Video: https://lnkd.in/eds2Buq8

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𝗘𝗻𝗱-𝘁𝗼-𝗘𝗻𝗱 𝗠𝗟 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻
 
A full ML project from start to finish.
Data prep, modeling, evaluation, and delivery.
 
Video: https://lnkd.in/ebx_dvtn

---

𝗠𝗟𝗢𝗽𝘀 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗧𝘂𝘁𝗼𝗿𝗶𝗮𝗹 (𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗩𝗶𝗲𝘄𝗲𝗿 𝗦𝗲𝗻𝘁𝗶𝗺𝗲𝗻𝘁)
 
Build a real ML pipeline using real data.
Feature engineering, modeling, and orchestration.
 
Video: https://lnkd.in/e9_xVb-Z

---

𝗬𝗼𝘂 𝗪𝗶𝗹𝗹 𝗡𝗢𝗧 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟 𝗶𝗻 𝟯 𝗠𝗼𝗻𝘁𝗵𝘀
 
A reality check on learning machine learning.
Focuses on process, depth, and consistency.
 
Video: https://lnkd.in/eRqYhJWK

---

𝗘𝗻𝗱-𝘁𝗼-𝗘𝗻𝗱 𝗥𝗲𝗴𝗿𝗲𝘀𝘀𝗶𝗼𝗻 𝗠𝗟 𝗣𝗿𝗼𝗷𝗲𝗰𝘁
 
A practical regression project walkthrough.
Covers evaluation, assumptions, trade-offs.
 
Video: https://lnkd.in/e2GEnb4N

---

𝗘𝘃𝗲𝗿𝘆 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱
 
A clear overview of common ML models.
 
Video: https://lnkd.in/eMW3YNKq

---

𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗚𝗿𝗮𝗱𝗲 𝗠𝗟 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗧𝘂𝘁𝗼𝗿𝗶𝗮𝗹
 
Focus on building ML systems that last.
Code quality, deployment, and maintainability.
 
Video: https://lnkd.in/eXYhdxgt

---

𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀)
 
A simple introduction to ML definitions and concepts.
 
Video: https://lnkd.in/eT3qrGBt
 
---

📌 Save this for your next project.
♻️ Repost this to help your network in data.

90% of analysts use only 10% of Pandas.

Master these 10 operations. Level up instantly.

When I started learning data analysis,
I thought Pandas was “too big” to master.

Turns out… you only need the core.

Here are the operations I use almost daily:

• 𝗟𝗼𝗮𝗱 𝗱𝗮𝘁𝗮 → pd.read_csv()
• 𝗜𝗻𝘀𝗽𝗲𝗰𝘁 𝗾𝘂𝗶𝗰𝗸𝗹𝘆 → .head(), .info(), .describe()
• 𝗦𝗲𝗹𝗲𝗰𝘁 𝗰𝗼𝗹𝘂𝗺𝗻𝘀 → df[["col1","col2"]]
• 𝗙𝗶𝗹𝘁𝗲𝗿 𝗿𝗼𝘄𝘀 → df[df["col"] > value]
• 𝗚𝗿𝗼𝘂𝗽 & 𝗮𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲 → .groupby().agg()
• 𝗖𝗿𝗲𝗮𝘁𝗲 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 → df["new"] = expression
• 𝗠𝗲𝗿𝗴𝗲 𝗱𝗮𝘁𝗮𝘀𝗲𝘁𝘀 → pd.merge()
• 𝗛𝗮𝗻𝗱𝗹𝗲 𝗺𝗶𝘀𝘀𝗶𝗻𝗴 𝘃𝗮𝗹𝘂𝗲𝘀 → .isna(), .fillna()
• 𝗦𝗼𝗿𝘁 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 → .sort_values()
• 𝗘𝘅𝗽𝗼𝗿𝘁 𝗰𝗹𝗲𝗮𝗻 𝗱𝗮𝘁𝗮 → .to_csv() or .to_excel()

That’s it.

If you can combine these properly, you can solve 80% of real-world problems.

The rest is practice and business thinking.

PS: Is Pandas your go-to library for data analytics?

📌 Follow Anas Riad for more content around data science

I was never supposed to become a Data Scientist.

Nothing about my path pointed there.

I tried medicine.
Then architecture.
Spent 5 years on a Master’s in industrial engineering.
Worked as a professional DJ at the same time.

Then I found data science.
Late. Unexpectedly.
And honestly… it made no sense.

I changed countries.
I doubted myself constantly.
I had to spend one full year just learning how to speak better.
Five years ago, I couldn’t even express myself properly in this language.

Now I work in data science.
And create content in that same language.

It wasn’t linear.
It wasn’t clean.
And the odds were clearly against me.

What made the difference wasn’t just Python or maths.

Being a good data scientist is not only technical.

It’s also:

→ Being reliable when things break
→ Understanding the business, not just the model
→ Thinking clearly when data is messy
→ Explaining results so people actually act
→ Saying “this approach failed” and learning fast

Yes, you still need:

→ Coding
→ Statistics
→ Probability
→ Solid fundamentals

But that’s only part of the picture.

What really helped me:

→ Perseverance
→ Belief (especially when confidence was low)
→ Hard work
→ Learning from the right people

Data scientists don’t all look the same.
And they don’t come from the same background.

If your path feels messy, slow, or “wrong”,
you might actually be building something stronger.

PS: Did you find your path on the 1st try?

80% of analyst tasks will automate.

Will you still be relevant in 2026?

⭐ Venkata Naga Sai Kumar Bysani and I broke this down simply  ⤵️ 

1️⃣ Work with AI, not against it
Copilot, Claude, automation tools. Use them well. Guide them. Validate outputs.

2️⃣ SQL alone won’t cut it anymore
Add Python. Learn ML basics. Understand how data pipelines work.

3️⃣ Understand the business deeply
Dashboards are easy. Translating numbers into revenue, risk, and strategy is rare.

4️⃣ Solve problems, not tickets
No one cares about the tool. They care about impact.

5️⃣ Build systems that run without you
Automate reports. Schedule pipelines. Create alerts. Sleep while your work runs.

6️⃣ Explain insights clearly
If leadership can’t understand it, it won’t matter.

7️⃣ Share your work publicly
Document what you’re learning. Visibility creates leverage.

-- -- -- 

The analyst role isn’t disappearing.
It’s evolving.

And the ones who adapt will win big in 2026.

💬 What’s your take?
Is the Data Analyst role shrinking or just becoming more strategic?

📌 Follow Venkata Naga Sai Kumar Bysani & Anas Riad for top-tier data content
♻️ Repost this post with your network to benefit

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Cosmo Shield ♾

Anas Riad

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