Data Scientist

Pay rate range - $80/hr. to $84/hr. on W2

Must Have

Causal Inference experience or experience on Causal Inference projects

Experiment Design (A/B testing, Randomized controlled trial (RTC), etc)

Python

Yrs Exp: 3+

REQUIRED SKILLS

Be able to communicate with stakeholders

Causal Inference experience or experience on Causal Inference projects

Experiment Design (A/B testing, Randomized controlled trial (RTC), etc)

BA in Economics or a similar field + 3 years of industry experience

Marketing measurements

PREFERRED SKILLS

PhD background in economics candidates would be great (no industry experience if they have just this)

If they have Deep Learning or AI that is great but no needed for this role

Job Description:

looking for a Data Scientist interested in solving one of the most challenging business problems in marketing measurement and developing cutting-edge ML models.

Working with our team of data scientists, applied scientists, research scientists, and economists, the scientists will design and develop scalable marketing measurements at Client and its subsidiaries.

This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business.

As a Data Scientist, you will be responsible for the development and production deployment of the cutting-edge measurement and optimization models, while collaborating with businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-channel marketing portfolios, estimating the impact on sparse customer actions, and scaling measurement solutions for WW marketplaces.

Unlike many companies who buy existing off-the-shelf marketing measurement systems, we are responsible for studying, designing, and building systems to serve clients' businesses.

Our team members have an opportunity to be at the forefront of marketing measurement thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, economists, and software developers in the business.

Responsibilities Include:

- Employ reduced form causal econometric methods to estimate the treatment effects of marketing.

- Utilize model estimates to provide insights to customers and drive business decisions.

- Build statistical models and tools using technical knowledge in causal inference, machine learning, statistical modeling, and other quantitative techniques.

- Understand the business reality behind large sets of data and develop meaningful analytic solutions.

- Innovate by adapting to new modeling techniques and procedures.

- Utilizing code (Python, R, etc.) for analyzing data and building statistical models to solve specific business problems

- Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters

- Collaborate with researchers, software developers, and business leaders to define product requirements and provide analytical support

- Communicating verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations