Staff Data Scientist Jobs

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

Stellar offers a carefully curated selection of wellness benefits and perks to our employees:

2+ Years experience in applied statistics (e.g. hypothesis testing, regressions, predictive modelings) or experimentation (e.g. A/B testing) in an industry setting

Deep experience as an Analyst in one of the following industries: Enterprise Software, SaaS, or Gaming/Monetization, Healthtech or Medtech industries

Experience working with at least 2 of the following business domains: Marketing, Customer Success, Product, Sales

Strong communication and presentation skills

Partner with product managers to create hypotheses, define quantitative goals, and design experiments for roadmap projects

8+ years of professional industry experience doing quantitative analysis.

Experience in schema design, data modeling, and building data pipelines.

Experience with a broad set of statistical and machine learning methods to build descriptive and predictive models.

Experience with designing and testing experiments.

Experience with data technologies that allow effective storage and analysis of large amounts of data (e.g. Spark, Presto, Hive, Hadoop, etc).

Experience with online data systems (e.g. relational databases, logging ingestion)

Translate recommendations into efficient action plans for senior management and department leaders

Collaborate with Product managers, Data Scientists, Engineers and Commercial leaders to deliver business impact

Demonstrable experience in Advertising or Gaming or e-commerce or high volume systems

Experience working with data using complex SQL; adept in at least one visualization tool such as Tableau

Analytical orientation and strong problem-solving skills,

Experience with at least one analytical programming language such as R or Python is a plus

Reframing of business activations and decision engines into ML/AI processes designed to achieve the near and long term business impact objectives.

Performing discovery, assessment, and ML/AI reengineering of existing decision engines to enable connected and harmonized intelligence to achieve targeted business outcomes.

Partnering with Retail Analytics to develop insights and pilot measurement of concepts in support of agile and iterative improvement processes.

You are passionate about driving ML/AI transformation for a Fortune 1 company!

You have an analytical mindset and a general understanding of AI/ML techniques.

You demonstrate being able to communicate horizontally and vertically across many stakeholders.

4+ years of professional industry experience doing quantitative analysis

Experience with statistical and machine learning methods to build descriptive and predictive models

More details about our company benefits can be found at the following link:

Partner with Slack Distribution teams to understand the drivers of our business and accelerate growth

Synthesize insights into crisp narratives and present to senior leadership

Develop frameworks for identifying patterns/trends in customer behavior and implement them in predictive scoring models

Experience in consumer lending, and/or knowledge of the consumer finance market, capital markets

5+ years work experience in increasingly senior analytical roles in technology and finance industry

Experience in credit analytics, valuation, and/or financial analytics development with Python, R, GSheet (AppScript), Excel (VBA), SAS

Experience working with large datasets, data modeling, and data pipelines using tools like Databricks, DBT, Looker, Redshift, Snowflake

Experience in coaching and mentoring junior team members on technical subjects

Demonstrated ability to work collaboratively and in deep partnership with cross-functional colleagues especially in Finance, Product, Data Engineering, Machine Learning teams

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.

Strong communication skills. Explains work and thought processes clearly and concisely.

Strongly desired: experience working in Growth function, in particular, experience working on SEO, logged out user experience, user activation and sharing/messaging.

Strong Experimentation background. Experience with working on experiments with network effects.

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.

Role 2: Assess the battery performance data and help define and verify requirements of quality and reliability under various operational scenarios

Excellent communication, organizational, and collaboration skills with the ability to convey information and content easily and effectively to stakeholders and customers

Working closely with Battery Products, Cell Development, and other teams at Form to:

Role 2: Integrate system reliability modeling with grid reliability modeling

Role 2: Build ML models for real-time forecasts unique to our technology for dispatch decisions

Interface with stakeholders across the various teams at Form to define analysis goals, and execute and communicate results

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.

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

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

At least 90% technical contributor, up to 10% management

Significant experience deploying and managing production-grade “Big Data” systems. Broad Knowledge of best practices in large- and small-scale data processing

Experience with ML frameworks such as TensorFlow or PyTorch

3+ years of experience with data scripting languages or statistical/mathematical software (Python, R, Matlab, etc.) and database languages (SQL, etc.)

Experience deploying Machine Learning solutions. Proficiency in data structure & algorithm design.

3+ years of hands-on experience in advanced machine learning topics including natural language processing, computer vision, or advanced statistical methods

Experience with A/B testing and ability to run rigorous experiments to produce scientifically sound recommendations.

Data driven storytelling experience with visualizations in Tableau, Power BI, etc.

You will collaborate with Business, Operations and Product Engineering to build data science products.

You will conceive and lead projects while being a hands-on builder of machine learning software components.

You will be a strategic thought partner for leaders across the organization on driving business impact through machine learning.

You will coach and mentor the next generation of strong engineers on the team.

Define quality standards and business rules for data management;

Coordinate project management activities and provide leadership in the design, implementation and maintenance of data management systems and documentation;

Manage implementation of Information System solutions;

Knowledge of Jira and Tableau

Knowledge of SQL Server and Oracle

Knowledge of Waterfall, Agile, Scrum, and Kanban