Senior Data Analyst - Twitter Service, Customer Analytics

  • Full-time

Company Description

Twitter Service Analytics team build real-time and offline solutions to make data accessible and reliable -- and then apply them to the most critical and fundamental analytical problems to guide TwS business decisions via observational analyses, trend analyses, modeling, and new measurement strategies.

Job Description

 

Twitter users generate many terabytes of data every day; The TwS analytics team is at the intersection of all this data and strives to make it meaningful to all business units within TwS. Analytics team build real-time and offline solutions to make data accessible and reliable -- and then apply them to the most critical and fundamental analytical problems to guide TwS business decisions via observational analyses, trend analyses, modeling, and new measurement strategies.

What You’ll Do:

We are trying to improve Twitter Service. To improve something, we need to be able to measure it. You will enable better measurements and ensure measurement accuracy so that we know where we are doing well and where we want to improve.

You’ll partner with product, technology, and ops leaders to turn business problems into data problems and demonstrate creativity by using existing data to solve those problems. You have at least 5 years of experience in applied data science and analytics, including hands-on development of metrics and dashboards, as well as end-to-end experimentation support.

  • Collaborate w/ business partners to find opportunities, understand objectives, and rationalize efforts to support strategic business objectives w/ both short-term and long-term deliveries in an environment with high SLA expectations.

  • Advanced - SQL, Python (descriptive / predictive models) and Tableau viz. Solid understanding of BigQuery, Presto, Vertica. 

  • Experience working with Web / Clickstream Analytics, Google Analytics, and (preferred) Medallia platform.

  • Own the end to end data science process, from initiation to deployment, and through ongoing communication and collaboration, sharing of results to partners and leadership.

  • Conduct quantitative analysis of experimental, and textual data to generate insights and drive decision making (ANOVA, Regression, Chi-Sq, AB, pre-post etc..)

  • [Optional] Ability to write Scalding jobs for data extraction and aggregation, and understanding of Data warehousing principles is a plus.

  • Write well detailed code that can be shared and used across teams, and can scale to be used in existing products

You will see a direct link between your work, TwS growth, and user happiness.

Soft skills:

  • Ability to communicate findings clearly to both technical and non-technical audiences and to optimal collaborate within multi-functional teams

  • We follow agile framework and processes. Hence, multi-functional collaboration, communication skills and a focus on delivering a phenomenal user experience are a must

  • You should be comfortable spearheading work plans, timelines and achievements

  • You have a sense of urgency, move quickly and ship things

Bonus Points:

  • You're experienced in metrics and experiential development

  • Experience in statistical methodology (multivariate, time-series, experimental design, data mining, etc.)

  • Industry experience (customer service or e-commerce is a plus)

Note: Potential exposure to critical or graphic content, including but not limited to vulgar language, violent threats, pornography, and other graphic images.

 

Qualifications

Soft skills:

  • Ability to communicate findings clearly to both technical and non-technical audiences and to optimal collaborate within multi-functional teams

  • We follow agile framework and processes. Hence, multi-functional collaboration, communication skills and a focus on delivering a phenomenal user experience are a must

  • You should be comfortable spearheading work plans, timelines and achievements

  • You have a sense of urgency, move quickly and ship things

Bonus Points:

  • You're experienced in metrics and experiential development

  • Experience in statistical methodology (multivariate, time-series, experimental design, data mining, etc.)

  • Industry experience (retail or service is a plus but not a prerequisite)

Additional Information

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