Lead Data Scientist

·        12 month contract with possible extension

·        Must be hands on

o   Set experimentation platform

o   Set up/read out

o   Do all analysis

o   SQL coding/scripting a must

·        Must have Stats Master’s or PhD

·        100 % remote (team mostly in Houston & UK)

·        Need to be able to run product experimentation end to end alone

·        Will be working in Customers and Products areas

o   Charging stations

o   Retail stores

o   B to C

·        In depth coding not req’d but must be excellent in SQL coding/scripting

·        Must have experience in real world situations

·        No Deep Learning or ML peeps

·        Must know A/B testing

·        Must be senior level (3-5 yrs doing this) and come from Tech Company (FAANG) because they do this sort of work

·        Could come from marketing analyst, product analyst, data analyst with the STATS education

·        There will be two tech interviews

o   Stats heavy interview

o   Product experimentation questions

o   SQL coding questions

·        Start date ASAP

Responsibilities:

• Part of a cross-disciplinary team, collaborating closely with product managers, business stakeholders, data engineers and other data analysts and data scientists in our B2C business areas.

• Set and advocate causal inference best practices and standards across our client

• Lead the design, analysis and interpretation of product experiments

• Identify and evangelize key performance indicators to be used in product experimentation

• Carry out causal inference from observational data

• Provide technical guidance on the design of our client's experimentation platform

• Present your findings to technical and business stakeholders • Actively mentor others, contribute to product experimentation and measurement learning and development paths

Qualifications:

• Bachelors, Masters or PhD in statistics or econometrics

• Deep statistical skills and at least 3+ years hands-on experience designing, running and interpreting A/B tests and analyzing observational data at scale in a real-world setting

• Strong programming (e.g. python) and SQL skills and understanding of software engineering best practices

• User-centric and product mindset

• Strong stakeholder management skills and ability to lead large organizations through influence

• Continuous learning and improvement mindset

• No prior experience in the energy industry required