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Career Building Tips From A Senior Data Scientist At Amazon

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Career Building Tips From A Senior Data Scientist At Amazon

Data science as a discipline – and specific skills in machine learning, analytics, and training algorithms – are in hot demand.

It’s a field that has exploded in popularity this past decade and is expected to create 11.5 million more new jobs in the U.S. alone by 2026.

So what’s it like to work as a data scientist, and what do you need to know if you’re thinking of starting your career there (or transitioning in later in life)?

I asked Naveed Ahmed Janvekar, a Senior Data Scientist from Seattle who works in Amazon’s fraud and abuse prevention team, to share his career journey.

Check out his story and the tips he has for those interested in pursuing a data science career.

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A Spark: Using Machine Learning To Solve Real-World Problems

What led you to a career in data science?

Naveed Janvekar: My interest in machine learning grew when I was working for Fidelity Investments as a Software Developer.

I had colleagues who were working as analysts with data to identify trends, which made me curious to explore this field. So I started analyzing my personal financial transactions to generate trends and insights.

This led to spending more time researching machine learning and how one could leverage it to model repetitive patterns to predict future outcomes and use it to our advantage to solve critical problems at scale.

In order to gain better expertise in this domain, I decided to pursue my Master’s in Information Science with a specialization in Machine Learning and Analytics.

Post-graduation, I worked at various U.S.-based companies in different analytical roles such as Analyst at Nanigans (a Boston-based AdTech startup), Business Intelligence Developer at KPMG, and Senior Data Scientist at Amazon.

The Role Of AI In Data Security

What role does machine learning play in your work as Sr. Data Scientist at Amazon?

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Naveed Janvekar: Machine learning and data science play a vital role in my job at Amazon.

In the abuse prevention team, we use various classification algorithms and deep learning algorithms to detect fraud and abuse on the platform.

Machine learning helps with achieving scalability and high precision detection as compared to traditional rule-based and/or heuristic-based abuse detection.

As abuse behaviors get complex over time, machine learning helps us with this challenge since we constantly re-train models with the latest abuse behavior/patterns.

I have filed patents for inventions related to the detection of emerging abuse on the platform using machine learning.

Communicating Data-Driven Insights

What unexpected skill or experience do you feel has helped you as a data science professional?

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Naveed Janvekar: The skill of gaining domain expertise and being able to effectively and simplistically communicate insights to business stakeholders has helped me the most as a data science professional.

When I began my data science journey, I put a lot more emphasis on technical details than being an effective storyteller.

But over the last few years, I’ve realized that being able to communicate narratives and insights from data science or machine learning is as important as implementing machine learning strategies.

Working Alongside Algorithms To Create Change

How should enterprises tailor their approach in this space moving forward?

Naveed Janvekar: In the past, fraud prevention was traditionally done using business heuristic rules.

If you observed a certain pattern appear frequently over time, you can put in a business rule to flag the same pattern in the future.

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However, this is a short-term solution. It doesn’t keep up with the evolution of fraud patterns.

This is where machine learning and AI come in and have changed the landscape.

Now, models are trained using historical data across multiple behaviors of fraud, making these models robust and helping algorithms learn complex behavior, which is much more difficult for humans to do.

Enterprises have started using machine learning in fraud detection. They must now focus on aspects such as automated re-training of models to capture the latest behaviors in fraud and make models highly precise.

This helps automate actions as a result of model output, rather than having human auditors required to evaluate suspicious entities that are flagged after the fact.

Working With Data And Algorithms Can Be Challenging

But what makes it exciting and fun?

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Naveed Janvekar: I’ve enjoyed feature engineering from data, which brings out my creative side.

Based on domain expertise, data scientists can munge the data in different ways to answer business stakeholders’ questions, perform exploratory data analysis, find correlations among variables, and conduct feature engineering for better model performances.

With respect to algorithms, I have always experimented with training different kinds on training datasets, conducting evaluations, and taking a deep dive into why certain algorithms work better than others.

This helps me gain a deeper understanding of these algorithms and situations where they work – and where they don’t.

All of this keeps the work fun and exciting for me.

Becoming A Part Of The Data Science Community

What’s one useful tip you’d want to share with data science beginners who are interested in its applications in marketing and commerce and may want to upskill themselves in this field?

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Naveed Janvekar: One useful suggestion would be to participate in research and inventions within the machine learning and data science domain.

Be part of working groups that are trying to solve problems in your area of interest using machine learning.

Contribute to their research, get peer feedback, publish papers, and file patents.

Through these mechanisms, you are actively contributing to the science community, constantly learning from peers, and upskilling yourself.

It’s also a good idea to have a data science mentor.

Keeping Up With SEO Trends

How does a data scientist stay up-to-date and informed in the field of SEO?

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Naveed Janvekar: In the field of SEO, machine learning helps with the understanding of queries, voice search, and personalization.

Data scientists can explore applying various state-of-the-art algorithms for SEO use cases to measure the efficacy of newer algorithms.

Doing this will keep data scientists up-to-date with the latest trends in the industry, as well as updating the machine learning stack in SEO-related firms.

There are various journals and conferences, such as the IEEE International Conference, on machine learning and applications to help you learn more about the latest machine learning trends.

It’s not directly SEO-related but will help you understand the technological advancements that will disrupt your space next.

More Resources:

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Featured Image: Courtesy of Naveed Janvekar




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How To Write ChatGPT Prompts To Get The Best Results

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How To Write ChatGPT Prompts To Get The Best Results

ChatGPT is a game changer in the field of SEO. This powerful language model can generate human-like content, making it an invaluable tool for SEO professionals.

However, the prompts you provide largely determine the quality of the output.

To unlock the full potential of ChatGPT and create content that resonates with your audience and search engines, writing effective prompts is crucial.

In this comprehensive guide, we’ll explore the art of writing prompts for ChatGPT, covering everything from basic techniques to advanced strategies for layering prompts and generating high-quality, SEO-friendly content.

Writing Prompts For ChatGPT

What Is A ChatGPT Prompt?

A ChatGPT prompt is an instruction or discussion topic a user provides for the ChatGPT AI model to respond to.

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The prompt can be a question, statement, or any other stimulus to spark creativity, reflection, or engagement.

Users can use the prompt to generate ideas, share their thoughts, or start a conversation.

ChatGPT prompts are designed to be open-ended and can be customized based on the user’s preferences and interests.

How To Write Prompts For ChatGPT

Start by giving ChatGPT a writing prompt, such as, “Write a short story about a person who discovers they have a superpower.”

ChatGPT will then generate a response based on your prompt. Depending on the prompt’s complexity and the level of detail you requested, the answer may be a few sentences or several paragraphs long.

Use the ChatGPT-generated response as a starting point for your writing. You can take the ideas and concepts presented in the answer and expand upon them, adding your own unique spin to the story.

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If you want to generate additional ideas, try asking ChatGPT follow-up questions related to your original prompt.

For example, you could ask, “What challenges might the person face in exploring their newfound superpower?” Or, “How might the person’s relationships with others be affected by their superpower?”

Remember that ChatGPT’s answers are generated by artificial intelligence and may not always be perfect or exactly what you want.

However, they can still be a great source of inspiration and help you start writing.

Must-Have GPTs Assistant

I recommend installing the WebBrowser Assistant created by the OpenAI Team. This tool allows you to add relevant Bing results to your ChatGPT prompts.

This assistant adds the first web results to your ChatGPT prompts for more accurate and up-to-date conversations.

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It is very easy to install in only two clicks. (Click on Start Chat.)

Screenshot from ChatGPT, April 2024

For example, if I ask, “Who is Vincent Terrasi?,” ChatGPT has no answer.

With WebBrower Assistant, the assistant creates a new prompt with the first Bing results, and now ChatGPT knows who Vincent Terrasi is.

Enabling reverse prompt engineeringScreenshot from ChatGPT, March 2023

You can test other GPT assistants available in the GPTs search engine if you want to use Google results.

Master Reverse Prompt Engineering

ChatGPT can be an excellent tool for reverse engineering prompts because it generates natural and engaging responses to any given input.

By analyzing the prompts generated by ChatGPT, it is possible to gain insight into the model’s underlying thought processes and decision-making strategies.

One key benefit of using ChatGPT to reverse engineer prompts is that the model is highly transparent in its decision-making.

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This means that the reasoning and logic behind each response can be traced, making it easier to understand how the model arrives at its conclusions.

Once you’ve done this a few times for different types of content, you’ll gain insight into crafting more effective prompts.

Prepare Your ChatGPT For Generating Prompts

First, activate the reverse prompt engineering.

  • Type the following prompt: “Enable Reverse Prompt Engineering? By Reverse Prompt Engineering I mean creating a prompt from a given text.”
Enabling reverse prompt engineeringScreenshot from ChatGPT, March 2023

ChatGPT is now ready to generate your prompt. You can test the product description in a new chatbot session and evaluate the generated prompt.

  • Type: “Create a very technical reverse prompt engineering template for a product description about iPhone 11.”
Reverse Prompt engineering via WebChatGPTScreenshot from ChatGPT, March 2023

The result is amazing. You can test with a full text that you want to reproduce. Here is an example of a prompt for selling a Kindle on Amazon.

  • Type: “Reverse Prompt engineer the following {product), capture the writing style and the length of the text :
    product =”
Reverse prompt engineering: Amazon productScreenshot from ChatGPT, March 2023

I tested it on an SEJ blog post. Enjoy the analysis – it is excellent.

  • Type: “Reverse Prompt engineer the following {text}, capture the tone and writing style of the {text} to include in the prompt :
    text = all text coming from https://www.searchenginejournal.com/google-bard-training-data/478941/”
Reverse prompt engineering an SEJ blog postScreenshot from ChatGPT, March 2023

But be careful not to use ChatGPT to generate your texts. It is just a personal assistant.

Go Deeper

Prompts and examples for SEO:

  • Keyword research and content ideas prompt: “Provide a list of 20 long-tail keyword ideas related to ‘local SEO strategies’ along with brief content topic descriptions for each keyword.”
  • Optimizing content for featured snippets prompt: “Write a 40-50 word paragraph optimized for the query ‘what is the featured snippet in Google search’ that could potentially earn the featured snippet.”
  • Creating meta descriptions prompt: “Draft a compelling meta description for the following blog post title: ’10 Technical SEO Factors You Can’t Ignore in 2024′.”

Important Considerations:

  • Always Fact-Check: While ChatGPT can be a helpful tool, it’s crucial to remember that it may generate inaccurate or fabricated information. Always verify any facts, statistics, or quotes generated by ChatGPT before incorporating them into your content.
  • Maintain Control and Creativity: Use ChatGPT as a tool to assist your writing, not replace it. Don’t rely on it to do your thinking or create content from scratch. Your unique perspective and creativity are essential for producing high-quality, engaging content.
  • Iteration is Key: Refine and revise the outputs generated by ChatGPT to ensure they align with your voice, style, and intended message.

Additional Prompts for Rewording and SEO:
– Rewrite this sentence to be more concise and impactful.
– Suggest alternative phrasing for this section to improve clarity.
– Identify opportunities to incorporate relevant internal and external links.
– Analyze the keyword density and suggest improvements for better SEO.

Remember, while ChatGPT can be a valuable tool, it’s essential to use it responsibly and maintain control over your content creation process.

Experiment And Refine Your Prompting Techniques

Writing effective prompts for ChatGPT is an essential skill for any SEO professional who wants to harness the power of AI-generated content.

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Hopefully, the insights and examples shared in this article can inspire you and help guide you to crafting stronger prompts that yield high-quality content.

Remember to experiment with layering prompts, iterating on the output, and continually refining your prompting techniques.

This will help you stay ahead of the curve in the ever-changing world of SEO.

More resources: 


Featured Image: Tapati Rinchumrus/Shutterstock

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Measuring Content Impact Across The Customer Journey

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Measuring Content Impact Across The Customer Journey

Understanding the impact of your content at every touchpoint of the customer journey is essential – but that’s easier said than done. From attracting potential leads to nurturing them into loyal customers, there are many touchpoints to look into.

So how do you identify and take advantage of these opportunities for growth?

Watch this on-demand webinar and learn a comprehensive approach for measuring the value of your content initiatives, so you can optimize resource allocation for maximum impact.

You’ll learn:

  • Fresh methods for measuring your content’s impact.
  • Fascinating insights using first-touch attribution, and how it differs from the usual last-touch perspective.
  • Ways to persuade decision-makers to invest in more content by showcasing its value convincingly.

With Bill Franklin and Oliver Tani of DAC Group, we unravel the nuances of attribution modeling, emphasizing the significance of layering first-touch and last-touch attribution within your measurement strategy. 

Check out these insights to help you craft compelling content tailored to each stage, using an approach rooted in first-hand experience to ensure your content resonates.

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Whether you’re a seasoned marketer or new to content measurement, this webinar promises valuable insights and actionable tactics to elevate your SEO game and optimize your content initiatives for success. 

View the slides below or check out the full webinar for all the details.

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How to Find and Use Competitor Keywords

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How to Find and Use Competitor Keywords

Competitor keywords are the keywords your rivals rank for in Google’s search results. They may rank organically or pay for Google Ads to rank in the paid results.

Knowing your competitors’ keywords is the easiest form of keyword research. If your competitors rank for or target particular keywords, it might be worth it for you to target them, too.

There is no way to see your competitors’ keywords without a tool like Ahrefs, which has a database of keywords and the sites that rank for them. As far as we know, Ahrefs has the biggest database of these keywords.

How to find all the keywords your competitor ranks for

  1. Go to Ahrefs’ Site Explorer
  2. Enter your competitor’s domain
  3. Go to the Organic keywords report

The report is sorted by traffic to show you the keywords sending your competitor the most visits. For example, Mailchimp gets most of its organic traffic from the keyword “mailchimp.”

Mailchimp gets most of its organic traffic from the keyword, “mailchimp”.Mailchimp gets most of its organic traffic from the keyword, “mailchimp”.

Since you’re unlikely to rank for your competitor’s brand, you might want to exclude branded keywords from the report. You can do this by adding a Keyword > Doesn’t contain filter. In this example, we’ll filter out keywords containing “mailchimp” or any potential misspellings:

Filtering out branded keywords in Organic keywords reportFiltering out branded keywords in Organic keywords report

If you’re a new brand competing with one that’s established, you might also want to look for popular low-difficulty keywords. You can do this by setting the Volume filter to a minimum of 500 and the KD filter to a maximum of 10.

Finding popular, low-difficulty keywords in Organic keywordsFinding popular, low-difficulty keywords in Organic keywords

How to find keywords your competitor ranks for, but you don’t

  1. Go to Competitive Analysis
  2. Enter your domain in the This target doesn’t rank for section
  3. Enter your competitor’s domain in the But these competitors do section
Competitive analysis reportCompetitive analysis report

Hit “Show keyword opportunities,” and you’ll see all the keywords your competitor ranks for, but you don’t.

Content gap reportContent gap report

You can also add a Volume and KD filter to find popular, low-difficulty keywords in this report.

Volume and KD filter in Content gapVolume and KD filter in Content gap

How to find keywords multiple competitors rank for, but you don’t

  1. Go to Competitive Analysis
  2. Enter your domain in the This target doesn’t rank for section
  3. Enter the domains of multiple competitors in the But these competitors do section
Competitive analysis report with multiple competitorsCompetitive analysis report with multiple competitors

You’ll see all the keywords that at least one of these competitors ranks for, but you don’t.

Content gap report with multiple competitorsContent gap report with multiple competitors

You can also narrow the list down to keywords that all competitors rank for. Click on the Competitors’ positions filter and choose All 3 competitors:

Selecting all 3 competitors to see keywords all 3 competitors rank forSelecting all 3 competitors to see keywords all 3 competitors rank for
  1. Go to Ahrefs’ Site Explorer
  2. Enter your competitor’s domain
  3. Go to the Paid keywords report
Paid keywords reportPaid keywords report

This report shows you the keywords your competitors are targeting via Google Ads.

Since your competitor is paying for traffic from these keywords, it may indicate that they’re profitable for them—and could be for you, too.

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You know what keywords your competitors are ranking for or bidding on. But what do you do with them? There are basically three options.

1. Create pages to target these keywords

You can only rank for keywords if you have content about them. So, the most straightforward thing you can do for competitors’ keywords you want to rank for is to create pages to target them.

However, before you do this, it’s worth clustering your competitor’s keywords by Parent Topic. This will group keywords that mean the same or similar things so you can target them all with one page.

Here’s how to do that:

  1. Export your competitor’s keywords, either from the Organic Keywords or Content Gap report
  2. Paste them into Keywords Explorer
  3. Click the “Clusters by Parent Topic” tab
Clustering keywords by Parent TopicClustering keywords by Parent Topic

For example, MailChimp ranks for keywords like “what is digital marketing” and “digital marketing definition.” These and many others get clustered under the Parent Topic of “digital marketing” because people searching for them are all looking for the same thing: a definition of digital marketing. You only need to create one page to potentially rank for all these keywords.

Keywords under the cluster of "digital marketing"Keywords under the cluster of "digital marketing"

2. Optimize existing content by filling subtopics

You don’t always need to create new content to rank for competitors’ keywords. Sometimes, you can optimize the content you already have to rank for them.

How do you know which keywords you can do this for? Try this:

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  1. Export your competitor’s keywords
  2. Paste them into Keywords Explorer
  3. Click the “Clusters by Parent Topic” tab
  4. Look for Parent Topics you already have content about

For example, if we analyze our competitor, we can see that seven keywords they rank for fall under the Parent Topic of “press release template.”

Our competitor ranks for seven keywords that fall under the "press release template" clusterOur competitor ranks for seven keywords that fall under the "press release template" cluster

If we search our site, we see that we already have a page about this topic.

Site search finds that we already have a blog post on press release templatesSite search finds that we already have a blog post on press release templates

If we click the caret and check the keywords in the cluster, we see keywords like “press release example” and “press release format.”

Keywords under the cluster of "press release template"Keywords under the cluster of "press release template"

To rank for the keywords in the cluster, we can probably optimize the page we already have by adding sections about the subtopics of “press release examples” and “press release format.”

3. Target these keywords with Google Ads

Paid keywords are the simplest—look through the report and see if there are any relevant keywords you might want to target, too.

For example, Mailchimp is bidding for the keyword “how to create a newsletter.”

Mailchimp is bidding for the keyword “how to create a newsletter”Mailchimp is bidding for the keyword “how to create a newsletter”

If you’re ConvertKit, you may also want to target this keyword since it’s relevant.

If you decide to target the same keyword via Google Ads, you can hover over the magnifying glass to see the ads your competitor is using.

Mailchimp's Google Ad for the keyword “how to create a newsletter”Mailchimp's Google Ad for the keyword “how to create a newsletter”

You can also see the landing page your competitor directs ad traffic to under the URL column.

The landing page Mailchimp is directing traffic to for “how to create a newsletter”The landing page Mailchimp is directing traffic to for “how to create a newsletter”

Learn more

Check out more tutorials on how to do competitor keyword analysis:

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