Director, Data Science, Blu.

Horizon Media•New York, NY

5d•$170,000 - $200,000•Hybrid

About The Position

The Director, Data Science is a strategic and technically skilled senior data scientist tasked with leading a variety of innovative and investigative projects on behalf of Horizon agencies and their clients. The role combines hands-on analytics expertise, people management and client-facing solution design and will define and influence Horizon data strategy and product direction. Leadership in this role often requires an ability to work cross-functionally with Client Architects and other teams key to the data acquisition through client presentation and will supervise a team ranging from 2 to 6 data scientists/analysts. As a result, they themselves must demonstrate a collaborative spirit and strong communication skills. They will be expected to become expert in all the data assets within Horizon’s proprietary Connected Marketing Platform called blu. and take ownership of specific data sources and client accounts.

Requirements

Master‘s degree in Computer Science, Statistics, Applied Mathematics, or a related field.
5-8+ years relevant experience, preferably in a media, marketing or digital advertising environment.
Proven experience using data to build audience strategies and glean insights
Working knowledge of Big and basic data mining routines a must.
SQL/Python /R knowledge a must.
Solid understanding of data technology integrations across data sources and ecosystems, and ability to troubleshoot.
Ability to work in a fast paced, multiple project environment on an independent basis and with minimal supervision.
A team player who can work collaboratively within the group and across business units/functions.
Proven management experience leading teams and direct reports.
Excellent organizational, communication and interpersonal skills with an ability to work effectively with non-technical stakeholders.

Nice To Haves

Advanced Statistics and/or PhD a plus.
Experience working with digital analytics and audience insights reporting (Campaign Manager/ GA/ Adobe/GA360) - a plus.

Responsibilities

Act as a collaborative partner to the business and all stakeholders
Proactively engage to solve problems for our clients and to strategically impact the growth and success of their business results
Managing internal timelines and set expectations on workstreams and projects
Participating in daily standups ensuring they and their team are meeting delivery commitments
Assigning tasks/projects to team members, estimate workload, understand capacity and utilization
Proactively identify and, when required, escalate issues and blockers striving to avoid business/client impact
Working with Client Architects and Data Solutions to outline all work required fulfill requests and generate outputs
Coach and manage performance of direct reports
Provide input to team training and development
Operate as a Product Innovator and become a Product expert and power user, to drive continuing improvement in both in the analysis and results being supported by AI and the continuing custom solutions built on top and around those
Experience with the ongoing operation and support of a Product in development and/or production
Ability to ensure design principles that scale and can be repeatable and/or extensible to other clients or industries
Experience with release management processes, including all levels of testing (Alph, Beta, QA, UAT)
Ability to define features, models, queries and requests with highest value of automation and incorporation into blu+ product
Ability to understand and leverage blu. structured and unstructured data
Identification of new analysis techniques for accounts and categories of accounts
Data transformation/mining and generation of insights to explain audience performance and inform optimization
Data join process between blu audiences, media exposure and conversion events to build feedback loops
Analysis of audience conversion to KPIs
Model creation to estimate contribution of attributes driving conversion
Validation of models used during the Audience Building process
Assessment of audience duplication and incrementality by channel, partner, or tactic
User/log level data extraction from delivery sources to create new audiences based on exposure to manage frequency
Database(s) querying to extract exposure events and create a new audience based on exposure by paid media channel (digital or linear)
Problem solving and development for new modeling and analysis techniques
Increasingly utilize AI solutions to inform and expedite some or all of the required analysis
Advanced knowledge of dimensions & metrics (people based, behavioral and media data)
Ability to understand and make sense of the relationships/connections across datasets
Knowledge of the data dictionaries and taxonomies of structured data sets
Understanding the applicability of research methods based on specific challenges
Extensive experience in ML and different techniques of supervised and unsupervised learning
ETL & EDA processes
Understanding of the complexity of working with Big Data