Research Data Scientist, Risk Quantification at Google

Sunnyvale, California, United States -

Full Time

Start Date

Immediate

Expiry Date

02 Mar, 26

Salary

189000.0

Posted On

02 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Statistics, Mathematics, Data Science, Engineering, Python, R, SQL, Statistical Analysis, Communication, Risk Analysis, Modeling, Data Gathering, Data Processing, Data Analysis, Business Problem Solving, Investigative Techniques

Industry

Software Development

Description

MINIMUM QUALIFICATIONS: * Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. * 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or 2 years work experience with a Master's degree). PREFERRED QUALIFICATIONS: * Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. * Experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases, and statistical analysis. * Excellent communication skills, with an ability to translate complex analysis into clear insights. ABOUT THE JOB: Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next. Our mission is to transform risk management within the company, making it data-driven and quantitative. We provide investigative expertise, objectivity, to solve some of the largest questions on how to address risks facing the company, enabling our partners to make optimal decisions for protecting Alphabet and its Users. The Risk Analytics and Data Science (RADS) team collaborates with risk and control owners across Google to quantify risk and drive data-based decisions. In this role, you will be working closely with cross-functional stakeholders to understand the business decisions they need to make, the limits of the data available, and how to translate their needs into a modeling framework. You will lead these projects end-to-end, building strong relationships with your partners to be able to understand the problems they need to solve and the data they can provide. You will have the chance to autonomously, or with assistance from your team, delineate and define risk analysis issues. This includes converting available information into actionable data and developing and deploying models and risk metrics. The US base salary range for this full-time position is $132,000-$189,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google [https://careers.google.com/benefits/]. RESPONSIBILITIES: * Partner with stakeholders in Product Management, Engineering and Operation teams to understand their domain and needs for risk analysis. * Conduct end-to-end model design that includes data gathering and requirements specification, processing, analysis, ongoing deliverables. * Make recommendations based on data and business context to advance risk and data understanding through each engagement. * Communicate results and impact of modeling choices to help stakeholders make optimal decisions. * Apply investigative techniques in novel ways to transform difficult data into useful information.

Responsibilities

Partner with stakeholders to understand their needs for risk analysis and conduct end-to-end model design. Communicate results and impact of modeling choices to help stakeholders make optimal decisions.