42 Pattern Data Scientist Jobs Hiring Near You

• Develop, deploy, and support real-time, automated, scalable data streams from a variety of sources into the data lake or data warehouse.
• Develop and implement data auditing strategies and processes to ensure data quality; identify and resolve problems associated with large-scale data processing workflows; implement technical solutions to maintain data pipeline processes and troubleshoot failures.
• Collaborate with technology teams and partners to specify data requirements and provide access to data.
• Tune application and query performance using profiling tools and SQL or other relevant query languages.
• Understand business, operations, and analytics requirements for data
• Build data expertise and own data quality for assigned areas of ownership.
• Work with data infrastructure to triage issues and drive to resolution.

• Bachelor’s Degree in Data Science, Data Analytics, Information Management, Computer Science, Information Technology, related field, or equivalent professional experience.
• 3-5 years of experience working with SQL.
• Familiarity with implementing modern data architecture-based data warehouses.
• Familiarity with data warehouses such as Redshift, BigQuery, or Snowflake and understanding of data architecture design.
• Strong communication skills (both in presentation and comprehension).
• Exposure to data visualization tools like Tableau or ThoughtSpot.

• Experience working with time series databases.
• Experience with SQL, including the ability to write stored procedures, triggers, analytic/windowing functions, and tuning.
• Knowledge of Snowflake.
• Familiarity with Big Data, non-relational databases, Machine Learning and Data Mining.
• Familiarity with cloud-based technologies including SNS, SQS, SES, S3, Lambda, and Glue.
• Familiarity with modern data platforms like Redshift, Cassandra, DynamoDB, Apache Airflow, Spark, or ElasticSearch.
• Understanding of Data Quality and Data Governance.

• Data Fanatics: Our edge is always found in the data.
• Partner Obsessed: We are obsessed with partner success.
• Team of Doers: We have a bias for action.
• Game Changers: We encourage innovation.

• Game Changers- A game changer is someone who looks at problems with an open mind and shares new ideas with team members, regularly reassesses existing plans and attaches a realistic timeline to goals, makes profitable, productive, and innovative contributions, and actively pursues improvements to Pattern’s processes and outcomes.
• Data Fanatics- A data fanatic is someone who recognizes problems and seeks to understand them through data, draws unbiased conclusions based on data that lead to actionable solutions, and continues to track the effects of the solutions using data.
• Partner Obsessed- An individual who is partner obsessed clearly explains the status of projects to partners and relies on constructive feedback, actively listens to partner’s expectations, and delivers results that exceed them, prioritizes the needs of your partners, and takes the time to create a personable experience for those interacting with Pattern.
• Team of Doers- Someone who is a part of team of doers uplifts team members and recognizes their specific contributions, takes initiative to help in any circumstance, actively contributes to supporting improvements, and holds themselves accountable to the team as well as to partners.

• Initial phone interview with Pattern’s talent acquisition team
• Technical Interview with a member of the team
• Video interview with a hiring manager
• Professional reference checks
• Executive review
• Offer

• Be prepared to talk about professional accomplishments with specific data to quantify examples.
• Be ready to talk about how you can add value and be the best addition to the team.
• Focus on mentioning how you would be partner obsessed at Pattern.
• Be prepared to talk about any side projects related to data and analytics.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.