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At Harnham, we want you to have the best recruitment experience possible and that’s why we work hard to provide a professional and quality experience. This ethos is how we retain so many of our loyal clients, as we believe that building relationships is an important step when recruiting. 

SAS software can help businesses manage their data from a variety of sources, allowing them to get the most out of it through a variety of functions ranging from storage to advanced analytics. SAS experts use this to gain valuable insights into how businesses can improve their strategies and help them target and reach the right audience.


UPGRADE YOUR BUSINESS WITH NEW TALENT

To get the most out of any SAS software your business looks to use, it’s best to employ an SAS expert who can utilize the more advanced options to develop even more ways to organize your data. Candidates looking for a job using SAS should have an expert knowledge of using the software including developing, implementing and tracking analytical strategies.

At Harnham, we know that communication is crucial. We make sure that we are fully responsive throughout the recruitment process, so that you know exactly how your search is progressing. We believe that this helps us to make the entire procedure successful for everyone involved, both client and candidate. 

Whether you’re looking to implement SAS software within your business, or you’re an expert looking to apply your skills then you should contact Harnham today. For a positive recruitment experience please give us a call.

For the East Coast and Mid-West teams please call 212-796-6070, or email newyorkinfo@harnham.com.

For the West Coast team call 415-614-4999 or email sanfraninfo@harnham.com.

Latest Jobs

Data Analyst - SAS - 6 Month Contract
Salary

US$240 - US$320 per day

Location

Philadelphia, Pennsylvania

Description

A healthcare consultancy with a number of new clients is looking for a Data Analyst to join initially on a 6 month contract with a possibility to extend.

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Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

Business Intelligence Is About Asking The Right Questions

You’ve dotted all the ‘Is’, crossed all the ‘Ts’. You’ve ensured your business priorities were aligned with your mission and objectives. But, how can you know if you’re on the right path, especially in light of today’s uncertainties. Your crystal ball may be in the cloud, but to find its clarity, you have to be asking the right questions. Below are three questions to consider moving forward. 1. How Collaborative Are We? As businesses shift online and teams expand globally, collaborative business intelligence streamlines decision-making. A combination of BI tools, software, and social technologies to inform, engage, analyze, and form insights of what customers want and need. This form of collaboration takes decision-making out of its siloes. Not unlike the Socratic method, collaborative business intelligence solves problems through shared information to find common ground. Using business intelligence software to provide opportunities for predictive modeling, visual analysis of data and business metrics, businesses analysts can interpret and inform, in a more efficient streamlined process. 2. How Secure is Our Data? Whether big business, small business, or medium business, no one is immune to cyberattacks. The ever- increasing rise of these attacks pinpoints just how important keeping data secure is for all businesses. Breaches cause not only monetary loss, but ultimately, consumer trust leading to more loss. The importance of Data security cannot be overstated.  Now that a majority of businesses are making flexible and remote work options available, it’s imperative businesses work to keep data secure. Consumers today are much more concerned today about how and why their Data is used, and many may decline to offer it, not wanting to put themselves at risk of a possible cyberattack.  3. What’s the Best Platform to Drive Actionable Insights from Our Analytics? Much like the trend of collaborative BI, businesses are focused on combining business processes and workflows into one platform, so everyone has access to the same Data. It’s within these platforms, that businesses cannot only determine what action to take and implement those actions all in one place. Platforms become the hub of the wheel and the spokes are analytics of a particular industry, business, or department in which insights can be implemented. Some platforms on the move include Sisense and Sharepoint. Google Analytics Intelligence (GAI) might be the most well-known especially if you’re just getting started asking the right questions for your business.  If you want insight into the state of your business, know any major consumer traffic changes, or want to know the probable conversion rate of web browsers to customers, GAI can help you get those answers. Because it uses machine learning to help, it’s important to know not necessarily what questions to ask, but how to ask them. How to Ask a Computer the Right Questions If you’ve been working in a collaborative BI team and asking each other questions based on the data you’ve collected, it may be a bit of a mindset shift for asking questions of a computer. So, how you phrase your question, what you want to know, and how you ask may require a bit of thought to find the answers you’re looking for. Below are a few guidelines to consider when posing the questions.Follow the TrendIf you want to know what’s trending in your business, you might ask: How many products were sold last week?How many customers did I have today?Where are my customers located?What time were the most customers shopping?  Which is Best? When you want to know what product is selling the most and through which means. Follow the performance. These questions might include: Which channel converted the most customers?Which product sold the most? Which product sold the least?Which hour was best for customer traffic? Compare and Contrast These are questions or commands that enable you to compare two sets of data side by side, such as how your business performed week to week, day to day, or year to year. While most questions begin with ‘which’ or ‘how’, the compare and contrast questions can get a bit more complex. In these questions, you begin with what you want to know such as conversion rate, revenue shares, traffic, or trend.  As this year comes to a close, what questions will you ask of yourself? Are you ready for a change? A new role? If you’re a business, what questions will you ask to move your company forward in the new year? If you’re interested in Big Data & Analytics, we may have a role for you. Check out our current opportunities or contact one of our expert consultants to learn more.  For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Kavya Kannan

Kavya Kannan

23. December 2020

How Machine Learning and AI Can Help Us See the Forest for the Trees

In the early days of 2020, Johns Hopkins, the CDC, the WHO, and a host of other public organizations banded together in collaboration. They were on a mission to ensure the world had real-time information to a virus that would forever chance the course of this year and the years to come. Which is great for those families with a computer in every home or every person with smartphone access. But what about the rest of the world? How do you ensure those people without access to basic needs lives can be improved? A health non-profit using AI and Machine Learning is aiming to do just this. But the Data is vast and the sheer numbers of people need to be corralled by someone into something the computers can read and make decisions on. Who would have thought Public Research and Data Science would come together in such a manner and in such an important time? Three Benefits of Data Science and Machine Learning in Healthcare According to a seminar given in September 2019, two research scientists explained to the CDC the promises and challenges using Big Data for public health initiatives. After explaining a few definitions and making correlations, the focus was soon on the benefits. The focus of Machine Learning is to learn data patterns.From the initial focus, patterns can then be validated to ensure they make sense.These patterns and validation of patterns can find links between seemingly uncorrelated factors such as the relationship between one’s environment and their genetics. To the scientists working with these scenarios, the decisions seem simple. Yet, when it comes to explaining them to laymen like policymakers, there can be a shift in understanding. This shift can lead to arbitrary and different findings which can affect medical decision making. Why? Could it be using Random Forests in linking the data could be confusing?  Data Classification is Not as Cut-and-Dried as a Work Flow or Org Chart If someone shows us a work flow or organizational chart, we understand immediately each task to be done in which order or who reports to whom. But in trying to link uncorrelated bits of information using decision trees, it can seem more like abstract art, more subjective than direct. Yet, it is those correlations which answer the bigger questions brought to bear by Research Scientists, Public Health Researchers, the Data Scientists, and AI working together to see the bigger picture. Decision trees, ultimately, are the great classifier. But there are a few things which need to be in place first. Yet, in the random forest model it’s not just one decision tree, it’s many. This is definitely a case where, if you done right, you will see the forest for the trees and at the same time be able to determine patterns in those trees. A bit counter-intuitive, but this is what stretches our minds to see correlations and patterns we might not see otherwise, don’t you think? So, what do you need to help make predictions?  Two Important Needs to Help Make Predictions Predictive power. The features you employ should make some sense. For example, without a basic knowledge of cooking, you can’t just throw random items from your refrigerator into a pot and expect it taste good. Unless of course, you’re making soup and all you have to do is add water.The trees and their predictions should be uncorrelated. If you’ve ever seen M. Night Shymalan’s Lady in the Water, there’s a little boy who can ‘read’ cereal boxes and tell a coherent story. A predictive coherent story. This is the layman’s version of random forests, their predictive nature, and ultimately, the scientists who can ‘read’ and explain the patterns. If you're looking for your first or next role in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our recruitment consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Tim Jonas

Tim Jonas

01. October 2020

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