By James Santagata
Principal Consultant, Career OverDrive!
I'm often asked by recent grads and soon to be grads what are some of the hotter positions out there? Positions which not only would be good for an entry level individual but positions upon which a person could build a solid and lucrative career?
Alternatively, some approach this by asking me what work skills could they quickly pick up which could then be used for them landa position like this.
Based on current demand and market trends, positions in Digital Marketing / Marketing Automation, Sales (sales is always hot) and Business Intelligence / Data Analyst / Data Science are hot.
Today, I'd like to suggest gaining the skills necessary to land a position in Business Intelligence, Data Analysis or Data Science.
Data Science will tend to be the more technical of these three positions, often requiring far deeper skills in statistically analyzing data but also in understanding how unstructured data is structured as well as how the data sets are interrogated. This often means some heavy or heavier database and programming chops are required.
For BI positions, it may be enough to interrogate data using a popular BI software tool, such as SAS or Cognos to query the data sets.
In any event, These positions, therefore, require three unique skills sets.
1. The ability to understand and structure, unstructured data.
2. The ability to query and interrogate databases and data sets.
3. The ability to analyze and apply statistical analysis to the data sets.
At the lowest entry level, one should gain a solid understanding of statistics, either business or social statistics and how to apply them.
At its simplest, I would learn to understand required sample sizes and how to determine them, the difference of correlation vs causation, the difference between descriptive stats and predictive and so on. Key concepts: multivariate analysis, regression analysis, R2, statistical significance, ANOVA, confidence intervals, Chi square, stochastics and an overview of Bayesian statistics.
For software skills, I would master Excel with special attention paid to the statistical functions as well as the use of pivot tables and I would get a solid understanding of how to use Tableau, SAS or SPSS.
I would learn the R language and some other scripting language for crunching data sets and/or which has a strong statistical library. Try Python/Pandas. If not, then Perl.
I would also familiarize myself with XML, SQL and know how to query database tables.
That's to get you a good position.
But to move into the data science position, I would do all of the above but really bone up even further on the states, much deeper, looking at Machine Learning for instance.
And for the software I would get hands on experience with hadoop, hive, STATA and read up on data mining.
The best news?
All of this can be learned on one's own or through various online sites learned at one's leisure for practically free.
It will take some time but it can be done quickly and a degree or even a certificate is not needed but, of course, can provide some very strong social proof.
Principal Consultant, Career OverDrive!
I'm often asked by recent grads and soon to be grads what are some of the hotter positions out there? Positions which not only would be good for an entry level individual but positions upon which a person could build a solid and lucrative career?
Alternatively, some approach this by asking me what work skills could they quickly pick up which could then be used for them landa position like this.
Based on current demand and market trends, positions in Digital Marketing / Marketing Automation, Sales (sales is always hot) and Business Intelligence / Data Analyst / Data Science are hot.
Today, I'd like to suggest gaining the skills necessary to land a position in Business Intelligence, Data Analysis or Data Science.
Data Science will tend to be the more technical of these three positions, often requiring far deeper skills in statistically analyzing data but also in understanding how unstructured data is structured as well as how the data sets are interrogated. This often means some heavy or heavier database and programming chops are required.
For BI positions, it may be enough to interrogate data using a popular BI software tool, such as SAS or Cognos to query the data sets.
In any event, These positions, therefore, require three unique skills sets.
1. The ability to understand and structure, unstructured data.
2. The ability to query and interrogate databases and data sets.
3. The ability to analyze and apply statistical analysis to the data sets.
At the lowest entry level, one should gain a solid understanding of statistics, either business or social statistics and how to apply them.
At its simplest, I would learn to understand required sample sizes and how to determine them, the difference of correlation vs causation, the difference between descriptive stats and predictive and so on. Key concepts: multivariate analysis, regression analysis, R2, statistical significance, ANOVA, confidence intervals, Chi square, stochastics and an overview of Bayesian statistics.
For software skills, I would master Excel with special attention paid to the statistical functions as well as the use of pivot tables and I would get a solid understanding of how to use Tableau, SAS or SPSS.
I would learn the R language and some other scripting language for crunching data sets and/or which has a strong statistical library. Try Python/Pandas. If not, then Perl.
I would also familiarize myself with XML, SQL and know how to query database tables.
That's to get you a good position.
But to move into the data science position, I would do all of the above but really bone up even further on the states, much deeper, looking at Machine Learning for instance.
And for the software I would get hands on experience with hadoop, hive, STATA and read up on data mining.
The best news?
All of this can be learned on one's own or through various online sites learned at one's leisure for practically free.
It will take some time but it can be done quickly and a degree or even a certificate is not needed but, of course, can provide some very strong social proof.
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