From Facilities Management to Finance?

[RufusDawes]

I currently have a job extracting and manipulating data from a database using various 4th gen database programming languages. I love number crunching and programming and I want to do this as a career. I want to do some sort of stats course which is designed for people from various disciplines who require statistical knowledge, these are readily available off-campus or online study mode. I don't know what it should cover or what courses are good.

https://www.open.edu.au/wps/portal/oua/what-study/qualification?WCM_GLOBAL_CONTEXT=/wps/wcm/connect/migration/oua2/what+to+study/qualifications/qualification_data/SWI_STA_GCE

I don't really know anything about this industry beyond my current role which is literally just extraction, manipulation and some simple analysis of data.

The type of role I might be interested in would be along the lines of cats(&&random_financial term&i, "analyst"); as they seem to be the only jobs evre advertised...

I'm also interested in the IT side of things. Basically anything which involves large amounts of data and being able to analyse it interests me. Please can any of you very smart people provide some help and guidance as I do not know anything.

Do I need a massively hardcore math background ? That will be diffficult for me, especially given that some days I already come home and my brain is about to essplode.. :(

I don't even really know if I have the ability to do this sort of thing long term or not...but I have pretty good job at the moment.

 

[cubozoan]

Hi folks

This is my first ever post on this forum so bear with me.

I live and work in the UK. So looking for UK answers really.

I have a physics degree but no honours :( I have been mostly working as a science technician in schools. Did try a teaching course but left the course early. With my daughter approaching her 1st birthday, I really need a proper career.

I need to decide wether to go back into teaching before new government change everything or start from scratch and go into bookkeeping or accountancy.

With mortgage and other financial commitments it will be a struggle to cope on a teaching bursary.

Any thoughts and experiences and advice would be greatfully received.

Regards

Andy

 

[h_bar]

Hi,

Wondering if anyone in here has any experience with "advanced" business analytics. These jobs appeal to me but I'm not sure if I have the right background.

My history - got my PhD in theoretical condensed matter physics in 2004. I knew I wasn't going to make it as a theorist, so I decided to flip the coin and got a postdoc doing basically the same work but on the experimental side - risky probably, but I felt like it was probably a last chance at staying in academia/research. Postdoc was something of a failure, mostly not my fault, but I didn't do much to make it better. After a year teaching upper-level physics courses, decided it was probably time to move on, as I had no research plan, and wasn't passionate enough about my field to go back to a post-doc.

I found it (surprisingly) hard to land a job, but I did end up getting a nice contractor job doing web analytics. The work was fine, mildly interesting, and it seemed that someone with a solid math/analysis background could really go far in analytics. A few more years doing mostly marketing analytics for a few different companies, and now I'm in the job market again (worked for a startup that basically went bust).

At this point, I'm very attracted to "advanced analytics," algorithm development, data-scientist, decision-science type jobs. The problem is I have a somewhat strange background that doesn't fit the profile for these jobs, which basically call for either software-engineer types, or hardcore statisticians/applied mathematicians/operations research. Every interview I have, I am told that my PhD in physics is very attractive, because of the problem-solving abilities, and because it is a bit different than the normal applicant, but I just don't have enough of what they are looking for to actually get the job.

I'm wondering if it is worth going back to school to build up a more solid statistics & programming background - as a physicist, I believe I can learn just about anything pretty quickly, but in reality these jobs require a pretty well-honed tool set that I just don't have. I'm of the opinion that, already with a PhD, more schooling is probably less useful than direct work experience, but if I can't get into the field I want, then maybe it is necessary...

Any thoughts? Thanks...

 

[MacLaddy]

Here in the very near future my educational endeavors will force me to make some changes as far as employment is concerned.

Right now I am a Facilities Manager, overseeing all maintenance and janitorial duties for several office complexes. However, I am also a part time ME Student at a local community college, able to only take about two classes at a time.

I have begun the process of applying to schools outside of my area, and the search for employment in those same areas has begun. Unfortunately though, these are small towns and do not have a lot in the way of facilities, so I am finding myself at a crossroads. Even if I could find a position similar to what I have now, I need something with a more flexible schedule that could accommodate me going to school full time if possible, but at least 3/4 time.

Now that I have completed all Mechanical Engineering level math and physics, are there any other potential lines of work I could/should be considering? I know absolutely nothing about finance or banking, but I am very good at crunching numbers and could learn quickly. If there is anyplace for me in that world, what are the titles? What terms should I be searching?

Also, I have a wife and two very small children (one isn't born yet) that I need to provide for. My wife will be able to go back to work eventually, but that will be at least two years from now. So minimum wage or entry level is probably not an option.

Any thoughts or advice will be greatly appreciated.

Mac

 

[rkr]

Posted here with permission from Greg since the job posting section is gone. Thanks PF!


Quant hedge fund in Cambridge, MA seeking full-time developers and researchers

Domeyard, LP is a start-up hedge fund based in Cambridge, MA. We deploy capital in a variety of asset classes, through the use of quantitative models and low latency trading strategies. Our firm is backed by the founding members of one of the largest quant funds in the world, which has over $55 billion in assets under management (AUM). Domeyard's founding team and early employees have affiliations with MIT and Harvard, and have received numerous accolades from the IEEE, American Institute of Physics, Putnam Competition, MCM, ISEF and 100 Women in Hedge Funds.

We are seeking additional developers and researchers to join us. We are a fast-growing company: you will influence the early decisions of the firm and have the opportunity to lead a team of developers within months. Your code will often be deployed to handle substantial risk capital. As a developer, you will often work with cutting-edge libraries and protocols that are poorly-documented, and as a researcher, you will often perform self-directed research. Feel free to show us any work that demonstrates your day-to-day interest in coding or science - we would love to see your academic publications, GitHub projects or StackOverflow answers. No financial experience is required.

Our firm has a flat structure and a casual dress code, and your starting salary will be no less than those of the founders. You will enjoy both the perks of joining a hedge fund partnership as well as those of a startup founding team. You will have the opportunity to travel and meet industry leaders, and will receive health and dental coverage. We welcome cultural diversity and are able to sponsor H1-B visas.

If any of the following job descriptions interests you, please contact Tommy Anderson at <careers@domeyard.com> with your resume.


------------------
// Algorithmic trading developer
Responsibilities:
• Implementing software for low latency trading.
• Designing message-oriented middleware and internal APIs to publish-subscribe platforms and databases.
• Integrating external protocols and APIs with our infrastructure.
• Identifying and managing performance bottlenecks.
• Developing tools (e.g. numerical libraries, GUIs) to improve research productivity.

Preferred qualities:
• Background in computer science, physics, mathematics, or a related engineering discipline.
• Proficiency with C/C++ in a UNIX environment.
• Experience with low-level optimization (e.g. memory hierarchy, instruction set architectures, lock-free algorithms, bus overheads, profiling) and multi-core parallelism.
• Knowledge of operating system internals (e.g. network stack, timers, scheduling, interrupt handling, virtual memory, file systems) and kernel source.
• Elegant coding style and good taste in API design.


// Network engineer
Responsibilities:
• Evaluating new technologies to accelerate low latency trading.
• Deploying and maintaining a high-availability environment consisting of servers and databases distributed across multiple data centers.
• Performance-testing and assembling of server hardware.
• Managing petabyte-scale databases.
• Assessing network security and conducting penetration tests.

Preferred qualities:
• Proficiency with C and shell scripting in a UNIX environment.
• Practical knowledge of high-availability server and network architectures (e.g. redundancy, automatic failover, replication, recovery).
• Experience with network and database administration (e.g. Cisco IOS configuration, packet processing, IPsec VPN setup).
• Familiarity with performance analysis tools (e.g. tcpdump, sar, iostat) and network/system monitoring tools.
• Knowledge of TCP/IP, multicast, routing and switching.


// Quantitative researcher
Responsibilities:
• Deploying low latency statistical arbitrage and electronic market making strategies for multiple time zones.
• Collaborating with developers to implement research and trading ideas.
• Modeling market microstructure and performing statistical analysis on large data sets.
• Designing and writing documentation for tools that improve research productivity or trading efficiency.

Preferred qualities:
• Background in any scientific, mathematical or engineering discipline.
• Extensive research experience and an intense passion for solving quantitative problems.
• Practical experience with writing software in C++, Python, or any other object-oriented programming language.
• Familiarity with or a strong willingness to learn LaTeX typesetting and declarative programming (e.g. SQL, Haskell).