远程工作雷达

洞察与分析策略师

Insights & Analytics Strategist

职能支持限定地区(需当地身份)与中国几乎无重叠,需长期倒时差
公司Digible
薪资$125,000 - $145,000/年
工作地点United States
地域资格限定地区(需当地身份)
时区要求与中国几乎无重叠,需长期倒时差
用工类型permanent
发布时间2026-08-05
数据来源4dayweek.io
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。
作息提示:与中国几乎无重叠,需长期倒时差。

## **我们是谁**

Digible 是一家成立于 2017 年的私营数字营销公司,致力于为多户住宅行业提供前沿解决方案。我们提供全套数字服务,以及 Fiona,我们的预测分析平台,这是业内首款同类产品。

在 Digible,我们自豪于协作、透明和真实的团队文化。自 2021 年以来,我们被列为科罗拉多州最佳工作场所之一,并在“多户住宅最佳工作场所”排名中位列第 8 名。从我们的招聘流程到全员会议和全体大会,我们的价值观贯穿我们所做的每一件事。

我们认为多样性推动创新,我们努力创造一个包容的环境,让每个人都能带着真实的自我来工作。如果你准备开启职业生涯中最出色的工作,我们很期待你加入我们的团队!

##### **核心价值观**

- **真实性。** 对待所有人,承诺以坚定和真诚的方式行动和沟通。
- **好奇心。** 相信对工作的深入根本的好奇心(“为什么”)对于公司创新和进化至关重要。
- **专注。** 集体意志,保持完全投入并最终对交付成果负责。
- **谦逊。** 认识并每天实践“我们”永远大于“我”的理念。
- **幸福感。** 做出决定,将热情和热爱我们所做的事情置于一切之上。

### **职位描述**

Digible 正在寻找一名 **洞察与分析策略师** 加入我们的数据团队。

我们的数据团队负责受控的语义层、Silver 和 Gold 数据模型,以及 Digible 其他部门所依赖的可信指标定义。这个职位位于该基础之上,但面向外部。它弥合了我们目前收集的数据与代理团队每天为我们的约 1,000 名多户客户所做的决策之间的差距。

你将深入挖掘当前未被充分利用的数据源,将其转化为客户和业务洞察,并直接与我们的代理解决方案团队合作,将这些洞察应用到实际客户账户中。这不是一个制作仪表板的职位,也不是纯粹的数据工程职位。可以把它看作是两者之间的连接纽带:你利用语义层的可信基础,加上尚未被操作化的数据,并与代理团队一起将两者付诸实践。我们会通过你在客户账户上影响的决策和结果来衡量你的成功,而不是

查看英文原文

## **Who We Are**

Digible is a privately owned and operated digital marketing company founded in 2017 with a mission to bring cutting-edge solutions to the multifamily industry. We offer a full suite of digital services, alongside Fiona, our predictive analytics platform, the first of its kind.

At Digible, we take pride in our collaborative, transparent, and authentic culture. Since 2021, we've been recognized as a Top Workplace in Colorado and secured the #8 spot in the Best Places to Work Multifamily rankings. From our hiring process to our All Hands meetings and Town Halls, our values are at the core of everything we do.

We believe diversity fuels innovation, and we strive to create an inclusive environment where everyone can bring their authentic selves to work. If you're ready to do the best work of your career, we'd love to have you on the team!

##### **Core Values**

- **Authenticity.** The commitment to be steadfast and genuine with our actions and communication toward everyone we touch.
- **Curiosity.** The belief that a deep and fundamental curiosity (the "why") in our work is vital to company innovation and evolution.
- **Focus.** The collective will to remain completely devoted and ultimately accountable to our deliverables.
- **Humility.** The recognition and daily practice that "we" is always greater than "I".
- **Happiness.** The decision to prioritize passion and love for what we do above everything else.

### **The Role**

Digible is looking for an **Insights & Analytics Strategist** to join our Data team.

Our Data team owns the governed semantic layer, the Silver and Gold data models, and the trusted metric definitions that the rest of Digible builds on. This role sits next to that foundation but faces outward. It closes the gap between the data we already collect and the decisions our agency teams make every day for our roughly 1,000 multifamily clients.

You'll dig into data sources that aren't being used well today, turn them into client and business insight, and work directly with our Agency Solutions team to put that insight into action on real client accounts. This isn't a dashboard-building role, and it isn't a pure data engineering role either. Think of it as the connective tissue between the two: you take the semantic layer's trusted foundation, add in data nobody has operationalized yet, and put both to work alongside the agency. We'll measure your success by the decisions and outcomes you influence on client accounts, not just the reports you hand off.

You'll report to our Director of Data and partner most closely with our Director of Agency Solutions, sitting within a roughly 20-person technology department. You'll also work with Analytics Engineering on data foundations and Data Science when a question needs deeper modeling.

#### **You'll Love This Job If You:**

- Embrace Digible's core values: authenticity, curiosity, focus, humility, and happiness
- Enjoy turning a pile of underused data (call recordings, CRM activity, client financials) into a clear, defensible insight
- Care as much about driving action as about being right. You're not satisfied until the insight changes what someone does
- Like being embedded with a business team, understanding their goals well enough to see their next question coming
- Move easily between analysis, storytelling, and stakeholder conversations
- Don't mind taking a manual, one-off analysis and turning it into a repeatable pipeline or report
- Already use AI tools as a normal part of how you explore, synthesize, and communicate
- Are comfortable in ambiguity and don't need someone else to define your scope for you
- Bring a customer-first mentality and genuine curiosity to your work
- Want the impact of your work to show up in a client outcome, not just a delivered report

#### **What You'll Do:**

- Operationalize Customer Analytics data. Build the pipeline and analysis to turn call and meeting intelligence into structured signal the agency can act on, closing today's biggest analytical blind spot
- Deliver client and account insight that goes beyond financial performance: client segmentation, health signals, and account-level narrative that support client dossiers and QBR prep
- Work embedded in agency workflows, close enough to Agency Solutions and account teams to understand their open questions, turning ad hoc requests into recurring, trustworthy analysis
- Turn insight into action. Don't stop at the finding; work with agency partners to define the recommended action, track whether it was taken, and follow up on the outcome
- Build analytics products that give account teams and clients a shared view of account health
- Be a bridge to the governed semantic layer by pulling from and helping extend the Analytics Engineering team's trusted metric definitions, rather than building parallel, ungoverned ones. Flag gaps back to that team instead of working around them
- Prove out ROI early. As a new, cross-functional role, you'll need a track record of concrete, attributable wins that justify continued investment

#### **How Success Will Be Measured:**

- **First 90 days:** A subset of customer analytics data operationalized into at least one repeatable analysis, and a first client insight delivered and acted on by the agency team
- **Days 90 to 180:** A small portfolio of insight-to-action wins tied to specific client accounts, with outcomes tracked, and clear handoff patterns established with Analytics Engineering for anything that should graduate into the governed semantic layer
- **Ongoing:** A growing, attributable track record of insights that changed what the agency did on a client account, not just insights that were delivered

#### **What You Should Have:**

- 4+ years of experience in an analytics, insights, or analytics-engineering role, ideally with direct exposure to a client-facing or agency/consulting environment
- Strong SQL skills and comfort querying a modern cloud warehouse (we use Snowflake) to go from raw data to insight on your own
- Experience turning unstructured or semi-structured data (call transcripts, CRM notes, support tickets) into structured, analyzable signal
- A track record of working directly with non-technical stakeholders: shaping a question, delivering an answer, and following through to action
- Comfort with BI and reporting tools for both client-facing and internal analysis
- Strong storytelling and written and verbal communication skills. You can make a data point land in a client or leadership conversation
- Real fluency with AI-assisted tools in your analytical workflow, not just occasional use
- A bias toward iterative, value-focused delivery. You'd rather ship a rough answer this week than a perfect one next quarter
- Comfort operating with real ambiguity in a role that is still being defined
- Comfort working without a Tech Lead or EM buffering your day-to-day technical direction. This is a standalone seat, not one embedded in an engineering pod

**What Will Set You Apart:**

- Experience in a digital marketing agency, multifamily/real estate, or other client-services environment
- Experience with conversation intelligence tools (Gong, Chorus, or similar) and turning them into structured analytics
- Experience building client segmentation or account health scoring models
- Familiarity with dbt, MetricFlow, or other semantic-layer tooling, even if you won't own it in this role
- Experience navigating a dotted-line or matrixed reporting structure without losing momentum

#### **Physical Requirements**

- Prolonged periods sitting at a desk and working on a computer
- Must be able to lift up to 15 pounds at times

This role is open to candidates located within the United States.

While this job description outlines the core expectations of the role, it's not a full list of everything you'll do at Digible. We believe in leaning in by hitting your key goals, sharing insights, and finding new ways to elevate performance, process, and client success.

#### **Pay, Perks and More!**

- **Salary Range: $125,000 to $145,000**
- 4-Day Work Week (32 Hour Work Week)
- WFA (Work From Anywhere)
- Discretionary Bonus
- We offer 3 weeks of PTO as well as Sick leave, and Bereavement
- We offer 11 paid holidays! (not counting ones that fall on Friday!)
- 401(k) + Match
- 75% Employer Paid Health Benefits (Medical, Dental, and Vision)
- Mental and Physical Wellness Reimbursement Benefit ($75/mo each)
- $1,000/year travel fund for employees who have been with Digible 3+ years
- Paid Parental Leave
- Dog-Friendly Office
- Monthly Social Events
- Weekly lunches and snacks for in office employees!

##### HEADS UP! We believe in transparency throughout our hiring process. To help us ensure a great fit, we'll ask you to share a few professional references during the hiring process who can speak to your experience and skills. It’s all part of our commitment to open, honest communication and our core values: Focus, Authenticity, Humility, Curiosity, and Happiness.

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