Senior Analyst, Digital Media

San Francisco, California
US$115000 - US$125000 per year

Senior Analyst, Digital Media
San Francisco, CA

$115-125k

Do you want the opportunity to join one of the largest independent agencies on the West Coast? If so, I'm looking for a digital media data expert to join a fast growth team as a Senior Analyst. A great opportunity to work in collaboration with a team of innovative industry leaders while taking responsibility for finding and identifying the trends, insights and recommendations that help drive partners marketing campaigns.

ROLE OVERVIEW - SENIOR ANALYST, DIGITAL MEDIA

  • Own the development of campaign planning items including: development of performance forecasts, defining key success metrics, guiding site tagging strategy, setting a reporting schedule, and creating report templates.
  • Ensure they have the right tools in place to measure against our campaign goals
  • Work closely with Account Managers, Media, and Ad Trafficking to ensure campaign-tracking mechanisms are put into place and data collection is functioning correctly
  • Work with other departments to ensure that marketing campaigns are optimized against data findings, including identification of best-performing media sites, ad creative versions, and offers
  • Facilitate consistent measurement and data reporting processes across multiple campaigns
  • Develop ongoing report presentations, highlighting insights, not simply sharing information

YOUR SKILLS AND EXPERIENCE

  • 2-5 years of experience as a data analyst, at an ad agency. Preference will be given to candidates with a deep familiarity with digital media, social media, web analytics, SEM, display, etc.
  • Experience with tag management solutions, such as GTM, for conversion tracking and site analytics is a plus
  • Familiarity with ad server platforms (i.e. DCM) and publisher data
  • Excel wizard. Experience with SQL is required. R or python is a plus
  • Familiar with Tableau or other visualization tools
  • Basic understanding of offline media research and measurement tools preferred (Simmons, MRI, Kantar/AdViews, YouGov, etc)
  • Aptitude for identifying key trends in data understanding why and what to do about it
  • Experience manipulating messy data and merging large complicated data sets

SALARY AND BENEFITS

The successful Senior Digital Analyst can expect a salary of $115-125k plus a comprehensive benefits package.

HOW TO APPLY

For more information about the role press "apply now".

KEYWORDS

Social Analytics, Analytics, Digital Analytics, Marketing Analyst, GTM, Site performance, site analytics, web analytics, SEM, Display, tag management, Tableau, SQL, media analysis, media analytics, digital media, DCM, DBM, DoubleClick, Google Analytics, Adobe Analytics, Media, Performance, Display, Programmatic, DMP, SEO, SEM

Send similar jobs by email
JP/SADB
San Francisco, California
US$115000 - US$125000 per year
  1. Permanent
  2. Media Analyst & Adtech

Similar Jobs

Salary

US$130000 - US$160000 per year

Location

New York

Description

One of 2019's fastest growing eCommerce start-ups is seeking a Senior Product Manager!

Salary

US$90000 - US$100000 per year

Location

Boston, Massachusetts

Description

This is an opportunity to work with c-level stakeholders and implement a brand-new digital A/B testing strategy to enhance the customer journey!

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.

When Pigs Fly or How Animal Organs Can Help Save Human Lives

Boston, Massachusetts is once again on the cutting edge of medical research and technology. From Electronic Health Records (EHR) to Machine Learning and predictive modeling of healthcare best practices to Computational Biology; the final frontier of genetic editing. We have come a long way in our quest to understand and improve our quality of life. In the face of cancer research, diabetes, and liver or heart failure, the world of Computational Biology opens the scientific doors to discovery and solution. This is a place for scientists to not only get to the heart of the matter, but to the core of the problem at the cellular level.  There is an old adage which states, “when pigs fly”, usually meaning some thing will never happen or is impossible. But what happens when the impossible becomes possible? The jury’s still out, but researchers are making great inroads in developing ways to save human lives using animal organs. Could Animal Organs Help Solve Donor Deficiency? There are over 100,000 patients in the U.S. waiting for a transplant operation and, for many, a this may be their only cure. Yet, our growing population and the sheer number of those waiting has created a donor deficiency of epic proportions.   Researchers have been working toward successfully transplanting organs from animals into humans. Not only has their study of stem cell technology grown over the years, but with the advent of bioinformatics, statistics, and Computational Biology, a new possibility has arisen. The chance to not only transplant organs from one species to another, but using another species to host the growing of transplantable human tissue. Getting the Framework Right Computational Biology is a broad discipline honed to a fine point. Using statistical modelling, it builds a wide variety of experimental Data and biological systems to understand algorithmics, Machine Learning, automation, and robotics. Its job is to ask and answer the question of how to efficiently gather, collate, annotate, search for information. But how can it do all this to determine appropriate biological measurements and observations? At the tipping point is the notion that to truly get a good picture of the problem, the frame must be in focus. And it is this, which is the most important task for Computational Biologists to solve before continuing their research. It’s a reminder to step back and look at the problem from another angle and to challenge assumptions turning “what if” on its head. Stretching, bending, and twisting toward a solution that might not otherwise have been thought without a framework in place in order to begin modelling the system. It is in this constant learning phase, Machine Learning applications with parameters set by the biologists, in which new information is processed, analyzed, and understood. This active learning model offers opportunities for applications to learn how to learn and will play a critical role in biomedical research now and in the future. And from this place, the second biggest problem to be solved enters the equation. Now, it’s time to refine the methods of how to solve the problem.   Next Steps As exciting as the possibilities are, like all things new, there are challenges. For example, not all animals will fit the bill for transplantation. The idea is to mimic as closely as possible the size and evolution of humans such as pig, sheep, or non-human primates.  But, at an even finer point of challenge are our own cell’s reactions and expressions and understanding why they act the way they do. Ultimately, it’s important to be sure information at the individual cell level is inferred with statistical references to verify findings. At the pixel level, not using a fine-tooth comb could mean your conclusions are wrong.  If you’re interested in Biostatistics, Bioinformatics, Computational Biology, Big Data & Analytics, we may have a role for you. We specialize in junior and senior roles. Check out our latest Computational Biology opportunities in our new Life Science Analytics specialism or our current vacancies for additional opportunities. Contact one of our recruitment consultants to learn more.  For our West Coast Team, call (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to newyorkinfo@harnham.com. 

Finance, Risk & Pricing: The Actuarial Analyst

Just because pricing deals with numbers, it doesn’t mean it’s exclusive to the financial sector. In our last few posts, we focused heavily on the role of Pricing Analyst, what it is and how to get there. This type of analyst role is more often found in the marketing arm of many companies and might also be known as Behavior Analyst, Customer Analyst, or something similar. However, there is another type of analyst sometimes confused with Pricing Analyst which falls squarely within the Finance sector. These roles might boast titles such as Risk Analyst, Financial Analyst, or Actuary. Often, it isn’t the title that speaks to the particular strengths of one type of role over another; it is the responsibilities and skill sets documented within the job description. Like Pricing Analysts, these professionals deal with numbers and pricing. However, their focus is on models, such as those required for mergers and acquisitions or how to set health insurance premiums looking at risk.  Looking for a Low to No-Risk Gig? Actuaries are in high demand. As a profession, it is one of the most diverse and tends to be more open to women and under-represented minorities. Though the focus is often on insurance and pension programs, Actuaries can find work in a number of industries including consulting firms, hospitals, banks, investment firms, and government.  As advisors who manage risk portfolios while analyzing historic and current data, these professionals are business-minded people with a mathematical basis. Using mathematics, statistics, and financial theory, they analyze the financial consequences of risk. The Masonic-esque Levels of Becoming an Actuary For individuals who are numbers focused and are interested in using their data, technical, and mathematical skills coupled with business acumen; the role of Actuary might be the perfect fit. However, there are steps or levels which need to follow to enter the profession. These are exam-based and work-experience levels and your salary increase incrementally with each step. To begin, a graduate with a high GPA and one exam under their belt may find the role quite lucrative. Each exam leads to the next level and enters you into an Actuarial Society. Depending on where and what you want to practice will determine which society you’ll sit the exam: Society of Actuaries (SOA) – focus is life and health insurance, pensions, and employee benefits. Casualty Actuarial Society (CAS) – focus is automobile, fire, and liability insurance as well as worker’s compensation. American Society of Pension Actuaries (ASPA) – focus is those in the pension field, particularly in relation to federal and state governments.  Each organization has its own exams and competition is fierce. Qualities sought beyond a high GPA and actuarial exam include: Good communication skills High technical ability A wide background from mathematics and statistics to the liberal arts Actuaries and analysts with an eye toward the financial and insurance sectors use their statistical skills to research, network, and connect the dots between discerned variables. The research begins with statistical modeling. Connect the Dots with Statistical Modeling In statistical forecasting models, the information gathered helps analysts make statements about real outcomes which haven’t yet come to pass. The model can then help identify what might influence these variables. An Actuary, Financial Analyst, or Risk Analyst may use a:  Merger Model (M&A) – This model is most often used in investment banking and corporate development. Think mergers and acquisitions. After all, someone has to decide the value of each company, then the basis of that value once they’re merged. Complexity varies widely in this model. Budget Model – This model is used in financial planning and analysis and helps set the budget for the coming year and the years to come. Focused heavily on a company’s income, these budgets are designed on a monthly or quarterly basis. Forecasting Model – This model is used to build a forecast of the budget model. Think of it as a building block as companies structure their budget and strategies using one or a combination of these models listed. Sometimes, the forecasting and budget model are combined. Sometimes they’re kept separate. These are only three of the ten types of models used in financial planning and analysis for any number of firms and industries. But, it’s the people behind the numbers who help businesses navigate what is best for their client, customer, and bottom line.  An Actuary is just one title those interested in the mathematical and statistical applications for business might find interesting. And like many of those in the Data Science field and higher tech applications, this role is in high demand. Are you the one companies are looking for? If you’re interested in finance, modeling, statistics, Big Data & Analytics, we may have a role for you. We specialize in junior and senior roles. Check out our current vacancies or contact one of our recruitment consultants to learn more.  For our West Coast Team, call (415) 614-4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast Teams, call (212) 796-6070 or send an email to newyorkinfo@harnham.com.

Recently Viewed jobs