Analytics Program Manager – Finance
San Francisco, California / $175000 - $200000
$175000 - $200000
San Francisco, California
Analytics Program Manager
San Francisco, CA (Hybrid)
This MedTech industry leader is looking to hire a Analytics Program Manager who will be the anchor of the team, responsible for partnering with the finance leadership team to strategize, design, and mature analytical capabilities. You will own and oversee financial data products and ensuring that they meet the needs of the business.
ROLE OVERVIEW - ANALYTICS PROGRAM MANAGER
- Lead the finance analytics program by managing the relationship with finance business partners
- Maximize enterprise analytics team velocity by optimizing work in progress and managing prioritization of analytics project roadmap
- Lead discussions with stakeholders to understand business problems and identify paths forward
- Design and promote processes and tools that improve efficiency and scalability of data operations
- Build a status reporting structure to track progress against different work tracks
- Drive standardization of key metrics across various business stakeholders to improve data governance maturity
- Present to senior leaders and executives with the ability to quickly gain trust by demonstrating the ability to ask the right questions and challenge the status quo
- Collaborate with solutions architects and data engineering to design data standards
SKILLS AND EXPERIENCE
- Minimum of a Bachelor's degree, ideally in Computer Science, Information Systems, Business Analytics or relevant field. A Master's is preferred.
- 5+ years' experience in analytics, business intelligence or data warehouse implementation
- Prior experience delivering BI / Analytics solutions across multiple stakeholders
- Excellent relationship building skills and demonstrated success in influencing without direct authority
- Experience with software development methodologies, project management tools, and analytics tools
- Outstanding verbal and written communication skills with the ability to engage and adapt to multiple audiences (engineers to C-level)
Using Data & Analytics to Create the Next Generation of Customer Loyalty Programs | Harnham US Recruitment post
Coupons. Codes. Vouchers. Points. Miles. The list of customer loyalty programs and what they provide is ever-evolving. Or if it isn’t, it should be. While travel and retail are the most well-known industries to offer these programs, other businesses such as healthcare and insurance are coming into the mix as well. Because while everyone knows the adage ‘Know Your Customer’, today, it means more than just their name and what they like to buy. It also means customer service, quality, and a reason to return.Though there are a host of technological advances to help businesses track their customers’ buying journey, behavioral habits, and collect their Data, there is one old-school advertisement to consider. Word-of-Mouth. Consider what and how we review products and services. It’s the digital version of word-of-mouth (read: reviews), Data can transform your customer loyalty programs, if you have the right strategy in place.The Next Generation of Loyalty ProgramsIf you’re just entering the market and want to design your first loyalty program, here are two questions you’ll want to ask yourself before you begin:Why do you want to design a customer loyalty program? If you just want to do what everyone else is doing, it won’t work. If you can’t clearly explain why you want to launch, then you’re not yet ready. Once you can identify the business purpose or objective, then you can think about next steps.How do you define success? What will you use to measure your objectives? Here’s where Advanced Analytics really come into play as you determine which customers you want to target, decide what you want them to do, and ensure your program is flexible enough to grow as your business grows as well as consistent with your messaging across brand channels.Whether emerging or evolving, your business may want to design or relaunch customer loyalty programs. If you’re relaunching because your loyalty program isn’t driving business. Ask yourself why. Options abound in today’s marketplace and the noise of places to buy products is only getting bigger. How you stand out from the rest will be a major driver in the years to come.What Customers WantIn establishing and developing new loyalty programs, it’s essential to begin with the end in mind, and the most important question to drive engagement is this: What do your customers want? Consider these statistics when planning your program, hiring your staff, and developing quality products and services to ensure your customers return again and again. After all, it’s much easier to retain a customer than to acquire a new one.So, while you may know your customer at the surface level and perhaps even a bit deeper through their behaviors and buying habits, Predictive Analytics can also help improve your loyalty program offerings. How? By helping you refine your program to better understand your customers.Want to know what drives your high-value customers? Use Predictive Analytics to determine what you want them to do by understanding your analytics of their buying behaviors and customer journey. You don’t want to give away too much, but you also want to provide value in your offerings and your customer service.Customer loyalty programs are as much about service and product as they are about word-of-mouth and retention. When someone recommends your product on one of their social media channels, they are acting as ambassador for your brand. These are your most loyal customers and what your program will look like in 2022 and in the years to come.If you’re interested in Digital Analytics, Advanced Analytics, or Data Science just to name a few, Harnham may have a role for you. Check out our latest Advanced Analytics jobs 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 firstname.lastname@example.org. For our Arizona Team, contact us at (602) 562 7011 or send an email to email@example.com. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to firstname.lastname@example.org.
Keepers of the Data Kingdom: the Analytics Engineer | Harnham US Recruitment post
If it seems the Data world is drilling down further into niche specialities, you’re right. Considering the swathes of information sent and received on a day-by-day, minute-by-minute, and second-by-second basis, is it any wonder? The sheer volume, depending on your business and what you want to know, requires not just a Data team, but must now include someone with a particular skillset, including the tech-savvy analyst who can speak to the executive team.So, who holds it all together? These swathes of information. Who organizes the information in a cohesive order, so anyone with a map, can make their own analyses? Enter the Analytics Engineer.What Makes an Analytics Engineer an Analytics Engineer?Though it’s a rather new speciality within the Data Scientist scope—think Machine Learning Engineer, Software Engineer, Business Analyst, etc—at its core, the definition of an Analytics Engineer is this: “The analytics engineer sits at the intersection of the skill sets of data scientists, analysts, and data engineers. They bring a formal and rigorous software engineering practice to the efforts of analysts and data scientists, and they bring an analytical and business-outcomes mindset to the efforts of data engineering.” Michael Kaminsky, consultant, and former Director of Analytics at Harry’s.In other words, analytics engineers, using best software engineering practices transform data through testing and documentation so that data analysts begin with cleaner data to analyze. As technically savvy as the engineer must be, they must also be able to explain to stakeholders what they’re looking at so they can formulate their own insights. Five Roles and Responsibilities of the Analytics EngineerLike all new niche specialities, there are core responsibilities to consider as well as that of skillsets required to either study to become an Analytics Engineer or to discover if you’re one already. How? Consider the questions you ask, your studies within Data Science, Computer Science, Statistics, and Math, and your balance between technical skills and soft skills. Below are five things to consider when thinking about this role:Programming language experience. Experience with programming languages like R and Python along with strong SQL skills which are at the core of this role. DBT technology knowledge. As the driving force behind the rise of Analytics Engineer as a separate role, it’s imperative anyone interested in pursuing it should have a firm grasp of DBT — the Data Build Tool — that allows the implementation of analytics code using SQL. Data tracking expertise using Git. Data modelling. Clean, tested, and raw data which allow executives and analysts to view their Data, understand it within the database or its warehouse. Data transformation. Analytics Engineers determine what Data is most useful and transform it to ensure it fits related tasks. It’s part of building the foundational layer so businesses can answer their own questions. Key Changes Leading to the Shift in Data RolesWith every technological advancement their comes new players to the field. The difference is here is that the job description already existed. We were only missing a title. But from the traditional Data team to the modern Data team, there are a few key changes that point directly to the rise of this niche field. Cloud warehouses (like Snowflake, Redshift, BigQuery) and the arrival of the DBT the foundational layer which can be built on top of modern data warehouses are the first two that come to mind. Then, the Software-as-a-Service (SaaS) tools like Stitch and Hevo are capable of integrating Data from a variety of sources, and the introduction of tools like Mode and Looker allows anyone interested in drawing insight from Data to do so on their own.Who Needs an Analytics Engineer? Small or Large Businesses?The short answer is it depends. But the general rule follows that while both large and small companies can benefit from having this professional on their staff, there are different things to consider. For example, a small business may be able to find what they need in a single individual. The Analytics Engineer is something of a jack-of-all-trades. Larger businesses, on the other hand, may already have a Data team in place. In this case, an Analytics Engineer adds to your team, something like an additional set of eyes increasing insight drawn from those large swathes of Data we spoke about earlier.So, what’s next for the role of Analytics Engineer? Who knows? The roles of any Data industry professional is constantly evolving. If you’re interested in Analytics Engineering, Machine Learning, Data Science, or Business Intelligence just to name a few, Harnham may have a role for you. Check out our latest Data & Analytics Engineering jobs 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 email@example.com. For our Arizona Team, contact us at (602) 562 7011 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
Is Product Analytics the new Digital Analytics? | Harnham Recruitment post
Following on from our exploration of what Digital Analytics is, and the exploration specifically of hiring Digital Insights Analysts in the North of England and Midlands, we wanted to take a look at Product Analytics, and how it differs from the standard Digital Analyst role.To help investigate the importance of Product Analytics in the current market, we have interviewed Nicky Tran, a Product Analyst at Virgin Media (Manchester).What Is A Product Analyst?In simple terms, a Product Analyst ‘’looks at the different products a company has, and then you are identifying which areas of the product can be improved or which areas can be optimised.” While Digital Analytics can inform the product lifecycle, the interesting aspect to this role is, that unlike a traditional Web Analyst role, it is more of a hybrid role. Nicky emphasised that it is ‘’an upcoming sector within the analytics community’’, providing an overlap between Digital Analytics, Customer Analytics and Data Science.The key skills and tools for this role are advanced SQL, Google Analytics, and AB testing. So how does this skillset differ from a traditional Web Analyst? Nicky suggests that while the core requirements are that of a Web Analyst, with a web role you would essentially just be using Google Analytics Data. However, as a Product Analyst, you would be using advanced SQL to access other data bases, and pull data from models, and therefore, “you are combining two sets of data to get a more insightful look”.Why Is Product Analytics Important, And Why Are They Now Becoming More Prominent On The Market?Similar to Digital Analytics roles, it is clear that with the impending digital transformation, companies are becoming increasingly data-led, especially with regards to their digital platforms (and products).As a result of the pandemic, the digital space is so much more important than ever before. Therefore, to stay competitive, and to really understand the products from the consumer perspective, companies have to provide the most personalised customer experiences to acquire and retain their consumers. As Nicky mentions, ‘It is definitely worth making an ‘inventory’ to see how to promote what you have – it is about personalising the customer journey’.What are employers looking for in a Product Analytics candidate?Product Analytics are great due to their hybridity. In the current market, where there are numerous jobs, and few candidates, a Product Analyst (technically strong in three areas) is a highly sought-after rarity.Businesses are becoming increasingly invested in Product Analytics and having a Product team that works alongside the Digital team can be beneficial; especially when companies need to stay competitive.What are Candidates looking for? Understanding the differences between a Digital Analyst, and a Product Analyst is key to understanding what a candidate is looking for. Nicky suggested that this Product Analyst role enabled her to be the ‘bridge’ between areas.So how does the future of a Product Analyst differ to that of the route of a Digital Analyst? For Nicky, this is one of the most important factors to being a Digital Analyst, as she has the option to go down the Data Science route in the future should she wish. The more technical skills she has as a Product Analyst means she is building up experience across different areas of Data & Analytics, giving her a slightly different career path, should she want to go down a more technical route.Why Choose A Product Analyst Role?“If you come from a technical background – maths, physics, computer science – and are interested in how the numbers are crunching, it is worth going into Product Analytics, as it needs a logical mathematics brain, to be able to convert it into a way which is useful to stakeholders.”From speaking to Nicky, it is clear that Product Analytics is an up-and-coming role that people don’t know enough about it. Therefore, if you are curious about Product Analytics, or any of the different roles the market has to offer at the moment, as an employer looking for help hiring, or a candidate actively or passively looking for work, Harnham can help. Take a look at our latest Product Analytics jobs, or get in touch for more information on how we can support your hiring needs.
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