From 47951eb0f5d61a71ec72cf27fc5a0f21cb88df15 Mon Sep 17 00:00:00 2001 From: Yanir Seroussi Date: Thu, 15 Feb 2024 10:08:39 +1000 Subject: [PATCH] Tweak home/about/consulting wording --- config.yml | 6 +----- content/about/index.md | 30 ++++++++++++------------------ content/consult/index.md | 20 ++++++++++---------- 3 files changed, 23 insertions(+), 33 deletions(-) diff --git a/config.yml b/config.yml index 1ddf8351d..5570fb352 100644 --- a/config.yml +++ b/config.yml @@ -42,7 +42,7 @@ params: hideFooter: true profileMode: enabled: true - title: 'Yanir Seroussi – Data & AI Expert*' + title: 'Yanir Seroussi – Data & AI Expert' subtitle: | [Consulting for](/consult/)... : startups and scaleups focused on growing while making a positive impact @@ -54,10 +54,6 @@ params: [Posting about](/posts/)... : data and artificial intelligence, and their role in driving positive business impact - -

- * Warning: Beware of self-proclaimed experts on the internet. Do your own due diligence. 🐳️ -

imageUrl: /home-profile.webp imageTitle: Yanir Seroussi's profile picture imageWidth: 278 diff --git a/content/about/index.md b/content/about/index.md index 2e7bd9b88..4b9b67410 100644 --- a/content/about/index.md +++ b/content/about/index.md @@ -6,43 +6,37 @@ cover: relative: true image: profile.jpg alt: Yanir Seroussi's profile picture -summary: About Yanir Seroussi, a full-stack data scientist and software engineer with over a decade of experience. +summary: About Yanir Seroussi, a hands-on data tech lead with over a decade of experience. comments: false # Avoid 404 when following the link for the final WP.com post. aliases: - /2021/11/06/migrating-off-wordpress-com-a-note-to-subscribers/ editPost: disabled: true -showToc: true disableShare: true --- -## Data & AI Expert? +With over a decade of experience across various data and engineering roles, the main theme of my career has been bringing data-intensive applications to production. This has included anything from solving isolated data problems to building systems that serve millions of users. With a proven capability to work independently and in teams, lead and mentor colleagues, and communicate with both technical and non-technical stakeholders, my focus is always on delivering business value. -As noted on [the homepage](https://yanirseroussi.com/), you should beware of self-proclaimed experts on the internet and do your own due diligence. I cringe putting the word _expert_ next to my name, as there's so much to know and learn, especially in a broad area like Data & AI. Still, underselling myself would also be silly. I'll let you be the judge. +My experience and formal education fall under three key areas: +- software engineering (15+ years; Computer Science BSc) +- data science / engineering (10+ years; Artificial Intelligence PhD) +- tech leadership (10+ years with startups and scaleups) -**⚡ New!** These days, I provide independent consulting services around Data & AI, focusing on startups and scaleups in the climate tech and nature-positive sector. See [my consulting page](/consult/) for details. +**⚡ New!** These days, I provide independent consulting services around Data & AI, focusing on startups and scaleups in the climate tech and nature-positive sector. See [my consulting page](/consult/) for details, or head directly to [my contact page](/contact/) if you have a problem you want to discuss. -## Obligatory self-promotional blurb +## Past work examples -I'm an experienced data scientist and software engineer with a deep background in computer science, programming, machine learning, and statistics. My work spans the full spectrum from solving isolated data problems to building production systems that serve millions of users. With a proven capability to work independently and in teams, lead and mentor co-workers, and communicate with both technical and non-technical stakeholders, I consistently deliver value to a variety of clients and projects. - -## Proof points - -Words are cheap. Any chatbot could generate a blurb like the above. Let's go deeper with a few highlights from my work: +Let's go deeper with a few highlights from my work: * **Building production systems that serve millions of users.** In [my work with Automattic](https://yanirseroussi.com/2021/10/07/my-work-with-automattic/), I re-architected and led the implementation of the company's unified online experimentation platform, and co-led the implementation of machine learning pipelines that had a significant impact on revenue from marketing campaigns. * **Solving isolated data & machine learning problems.** I'm [a retired Kaggle competition master](https://www.kaggle.com/yanirseroussi), having [ranked in the top ten of the five competitions I participated in](https://yanirseroussi.com/kaggle/). I've also worked on various other problems throughout my career, but many of them haven't resulted in public artefacts – such is the nature of commercial data. -* **Software engineering and programming expertise.** My undergraduate degree was in computer science, with a focus on software engineering. I graduated first in class from [the Technion – a top Israeli university](https://en.wikipedia.org/wiki/Technion_%E2%80%93_Israel_Institute_of_Technology). My early career included software engineering work with big tech companies (Intel, Qualcomm, and Google). I chose to work with startups after my PhD, before going back to a medium tech company (Automattic), and then [returning to the startup and freelancing worlds](https://yanirseroussi.com/2022/06/06/the-mission-matters-moving-to-climate-tech-as-a-data-scientist/). All my roles included a substantial hands-on coding component. I take software engineering seriously and strive to keep on top of and apply best practices, as [solid software is the foundation of all data work](https://yanirseroussi.com/2014/08/17/datas-hierarchy-of-needs/). -* **Artificial intelligence and data science expertise.** In my PhD I formally specialised in artificial intelligence. As the term _artificial intelligence_ was falling out of favour when I submitted my thesis in 2012, I also say that my PhD is in _data science_ (which may be decreasing in popularity in 2023). Either way, it resulted in [some publications in top venues](https://yanirseroussi.com/phd-work/) and [won an award for the best thesis in my faculty](https://www.monash.edu/news/articles/top-of-the-class) at [Monash – a leading Australian university](https://en.wikipedia.org/wiki/Monash_University). Personally, I don't think it's a big deal, but people seem to love PhDs and other credentials! Since my PhD, I've continued learning and honing my skills, as reflected by [posts on this site](https://yanirseroussi.com/) and [my LinkedIn profile](https://www.linkedin.com/in/yanirseroussi/). +* **Software engineering and programming expertise.** My undergraduate degree was in computer science, with a focus on software engineering. I graduated first in class from [the Technion – a top Israeli university](https://en.wikipedia.org/wiki/Technion_%E2%80%93_Israel_Institute_of_Technology). My early career included software engineering work with big tech companies (Intel, Qualcomm, and Google). I chose to work with startups after my PhD, before joining a unicorn scaleup (Automattic), and then [returning to the startup and freelancing worlds](https://yanirseroussi.com/2022/06/06/the-mission-matters-moving-to-climate-tech-as-a-data-scientist/). All my roles included a substantial hands-on coding component. I take software engineering seriously and strive to keep on top of and apply best practices, as [solid software is the foundation of all data work](https://yanirseroussi.com/2014/08/17/datas-hierarchy-of-needs/). +* **Artificial intelligence and data science expertise.** In my PhD I formally specialised in artificial intelligence. As the term _artificial intelligence_ was falling out of favour when I submitted my thesis in 2012, I also say that my PhD is in _data science_ (which was decreasing in popularity a decade later). Either way, it resulted in [some publications in top venues](https://yanirseroussi.com/phd-work/) and [won an award for the best thesis in my faculty](https://www.monash.edu/news/articles/top-of-the-class) at [Monash – a leading Australian university](https://en.wikipedia.org/wiki/Monash_University). Personally, I don't think it's a big deal, but people seem to love PhDs and other credentials! Since my PhD, I've continued learning and honing my skills, as reflected by [posts on this site](https://yanirseroussi.com/posts/) and [my LinkedIn profile](https://www.linkedin.com/in/yanirseroussi/). ## Outcomes beat job titles -One of the downsides of working in an ever-changing field and accumulating a broad range of experiences is that it's hard to summarise with a concise title. For example, being a data scientist [used to imply having strong software engineering skills](https://yanirseroussi.com/2014/10/23/what-is-data-science/), but [this has changed over time](https://yanirseroussi.com/2023/06/30/was-data-science-a-failure-mode-of-software-engineering/). It's a similar story with the decline and rise of artificial intelligence. In an ideal world, I'd be able to let my work speak for itself, but we don't live in such a world (in fact, [human work is obsolete in my ideal world](https://yanirseroussi.com/2023/04/21/remaining-relevant-as-a-small-language-model/)). In our world, people search for keywords and have different understandings of concepts, e.g., they may want "an AI solution" to a problem that can be solved with deterministic software engineering. Or they may believe they need an AI Engineer rather than a Data Scientist, when a few years ago it'd have been the opposite (as I'm writing this in 2023, you could replace the words _data science_ with _artificial intelligence_ across my historical posts and much of what I wrote would still hold). +One of the downsides of working in an ever-changing field and accumulating a broad range of experiences is that it's hard to summarise with a concise title. For example, being a data scientist [used to imply having strong software engineering skills](https://yanirseroussi.com/2014/10/23/what-is-data-science/), but [this has changed over time](https://yanirseroussi.com/2023/06/30/was-data-science-a-failure-mode-of-software-engineering/). It's a similar story with the decline and rise of artificial intelligence. In an ideal world, I'd be able to let my work speak for itself. In our world, people search for keywords and have different understandings of concepts, e.g., they may want "an AI solution" to a problem that can be solved with deterministic software engineering. Or they may believe they need an AI Engineer rather than a Data Scientist, when a few years ago it'd have been the opposite (as I'm writing this in 2023, you could replace the words _data science_ with _artificial intelligence_ across my historical posts and much of what I wrote would still hold). Anyway, whether you're trying to navigate Data & AI terminology or solve specific problems, I can probably help. As noted in [my consulting page](/consult/), my aim is to get to the root of business problems and iteratively implement pragmatic solutions. The taxonomy of Data & AI professionals is only relevant if I'm helping you hire a team. {{< figure src="mlops-roles.png" width="500" height="433" caption="A subset of roles I've performed in one way or another.
Source: [Machine Learning Operations (MLOps): Overview, Definition, and Architecture](https://ieeexplore.ieee.org/document/10081336)." alt="Venn diagram showing different MLOps-related roles: Data Scientist, ML/MLOps Engineer, Backend Engineer, Data Engineer, DevOps Engineer, and Software Engineer" >}} - -## Contact me - -See [my contact page](/contact/). diff --git a/content/consult/index.md b/content/consult/index.md index 84ff8a561..3691d2917 100644 --- a/content/consult/index.md +++ b/content/consult/index.md @@ -15,29 +15,29 @@ disableShare: true This is a high-level overview of my approach to consulting and the sort of problems I can help with. Feel free to [contact me](/contact/) for more details. -## Principles - -When approaching consulting engagements, I aim to follow these key principles: - -- Getting to the root of business problems. -- Iteratively implementing pragmatic solutions. -- Saying what I'll do, doing what I said, and communicating if anything changes. - ## Offerings With [my broad experience in data science, software engineering, and artificial intelligence](/about/), I can help in a variety of situations. My key offerings are: - Short one-off advisory sessions to address specific challenges and questions ([book paid call](https://talkw.me/@yanir)). -- Longer engagements to tackle data & AI problems, which start with problem discovery and lead to hands-on implementation work ([contact me to discuss](/contact/)). +- Longer engagements to tackle data & AI problems, which have two components: (1) problem definition and strategic planning; and (2) hands-on implementation work ([contact me to discuss](/contact/)). - Mid-to-long term engagements as a Fractional Chief Data & AI Officer for startups and scaleups (see [slide deck](/fractional-chief-data-officer/#/) for details). +## Principles + +When approaching consulting engagements, I aim to follow these key principles: + +- Getting to know you and the root of your business problems. +- Iteratively implementing pragmatic solutions. +- Saying what I'll do, doing what I said, and communicating if anything changes. + ## Examples Examples of the above offerings: - A short call to discuss an ongoing computer vision project, where the client was unsure the consultant they've retained was on the right path. I provided advice on where they should focus, based on my experience with best practices in such projects. - An [internal consulting project with Automattic](https://data.blog/2019/01/15/how-to-increase-retention-and-revenue-in-1000-nontrivial-steps/), where the aim was to increase WordPress.com customer retention rates. Artefacts from this project are still in use by the company five years later. -- I served in data & AI leadership roles with multiple startups. While those weren't fractional, a clear theme is that it's hard for non-data people to make the first data hires and give them the right tasks. These are the sort of items I can help with fractionally. +- I served in data & AI leadership roles with multiple startups. While those weren't fractional, a clear theme is that it's hard for non-data people to make [the first data hires](https://yanirseroussi.com/2024/02/05/substance-over-titles-your-first-data-hire-may-be-a-data-scientist/) and give them the right tasks. These are the sort of items I can help with fractionally. ## Ideal clients and areas