Staff Data Scientist Jobs in California

7+ years industry experience and an advanced degree in a quantitative field

Experience with communicating the results of analyses to executives and cross-functional teams to influence the strategy

Experience in technology, financial services and/or a high growth environment is advantageous

Ability to perform statistical analysis to drive data-informed decisions

Collaborate with partners from engineering to customer experience to inform strategic builds of essential compliance program elements

Expert level abilities in SQL and data analysis/visualization tools (i.e. Tableau, Looker)

Deep experience using data to solve complex, ambiguous problems

Vision to define problems and manage projects in a fast-­paced, evolving organization

Paid Life insurance, AD&D, and disability benefits

Perform deep dive analysis into different customer segments and/or products to identify pockets of compliance risk

8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data.

Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams.

Experience leading key technical projects and substantially influencing the scope and output of others.

Experience in the strategic analytics side of data science: shaping decisions rather than just building models.

What Skills Are Ideal But Not Required

Information regarding the culture at Pinterest and benefits available for this position can be found here.

You are experienced with agile methodologies using project planning and tracking management tools e.g., JIRA

You are skilled in Python. R, Scala are optional.

You are experienced in basic ETL practices. SQL experience is required, working experience in SparkSQL or PySpark is preferred.

You have experience with cloud environments including Azure, Google Cloud, etc.

Support the development of the Customer Decision Engine. Provide Causal Inference capabilities to cover the entire customer shopping journey.

Identify data collection opportunities to better understand the customer/associate experience. Support the build out of data feature store.

Present and visualise results in a clear and concise way to senior management for decision making.

Able to show good communication skills, and experience in visualising and reporting learnings.

4+ years experience as a data scientist in a technology company

Experience with a broad set of statistical and machine learning methods to solve and optimize critical business problems and metrics

Prior experience in advertising data products.

Leverage understanding of metrics, testing methodology and business strategy to help define the roadmap of the company.

Help manage and analyze existing cardholder portfolio covering spend engagement, balance stimulation, and good payment behaviors

Present analyses to Credit Card and Finance business leaders.

Proven track record of end-to-end experience in building analytical frameworks to inform business strategy;

5+ years of experience working in an analytics, business strategy, or related role in the credit card industry;

Knowledge and understanding of statistical and econometric modeling methods for significance testing and causal inference.

Effective communication and presentation skills and ability to explain complex analyses in simple terms to business leaders;

PhD in Statistics, Operations Research, Industrial Engineering and Mathematics or other quantitative fields with 3+ years of relevant work experience.

Strong knowledge of mathematical programming modeling, optimization, and machine learning.

Demonstrated production-level coding and programming abilities.

Experience of building large-scale Machine learning (deep learning and reinforcement learning) or optimization driven products.

Work with operations and product stakeholders to understand business needs and interpret them with scientific languages.

Independently develop Proof-Of-Concepts models of solves sequential decision making processes.

Strong background in statistics, either from academic research or industry experience

Advanced statistical programming skills, e.g., in Python or R

Experience manipulating, visualizing, and interpreting big data

PhD in statistics, math, physics, or another quantitative research area

Ability to interpret and work with data in the presence of ambiguity (e.g., confounding factors, data sparsity or quality challenges),

Willingness, ability, and patience to understand highly complex systems

Build and maintain complex dashboard reports for scalability, manageability, extensibility, performance, and re-use.

Influence and educate the team with your experience, idea and learning.

Bachelor's Degree or Master’s degree in Computer Science (or related field) and 8+ years of experience

Experience leveraging big data technologies such as Hive, Hadoop, Spark

Experience building and maintaining data pipelines and architecture.

Experience with visualization tools for data reporting such as Tableau, Looker

Synthesize data into succinct presentations that influence senior management decision making

Knowledge of statistical modeling or machine learning is preferred but not a requirement

8+ years of relevant work experience in growth or marketing capacity, with demonstrated experience developing and analyzing marketing campaigns

Industry experience in Banking, Brokerage, Credit Card and Marketing Analytics highly desired

Intellectual curiosity and aptitude to pick up new technical skills

Strong programming skills in SQL, Python and proficiency in Tableau