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In the ever-expanding landscape of technology, data has emerged as the lifeblood of innovation, driving decision-making processes across industries. As businesses strive to harness the power of data, the demand for skilled professionals capable of extracting actionable insights continues to surge. Among the most sought-after roles in this data-driven era is that of a Data Scientist. In the United States, the pursuit of excellence in data science has given rise to a multitude of opportunities for individuals passionate about transforming raw data into meaningful narratives.

This article explores the landscape of Data Scientist openings in the US, shedding light on the diverse and exciting possibilities that await those keen on navigating the world of data analytics.

PitchBook

Job Responsibilities:

Work with cross-functional teams to analyze and evaluate data on customer behavior.

Create and deploy innovative data models and algorithms to gain valuable insights.

Predictive and prescriptive analytics may be used to lead data-driven initiatives for improving the customer journey.

Construct and maintain complex datasets derived from customer interactions and engagement. Communicate actionable insights to multiple stakeholders, demonstrating the impact of various business segments on Sales, Customer Success, and overall company.

Keep abreast of market trends and develop analytics methodologies to continually improve our analytics skills.

Mentoring and advising junior data scientists in the team

Customer and marketing data should be analyzed to find patterns, trends, and opportunities throughout the customers lifetime.

Investigate consumer touchpoints and interactions to learn about their preferences and behavior.

Create predictive models that estimate consumer behaviors like churn, lifetime value, conversion rates, and buy proclivity.

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US Foods

Responsibilities:

You will be required to do the following as an Associate Data Scientist:

Data Preparation: Extract data from diverse databases; do exploratory data analysis; cleanse massage, and aggregate data.

Best Practices and Standards: Ensure that data science features and deliverables are adequately documented and executable for cross-functional consumption.

Collaboration: Work with more senior team members to do ad hoc analyses, collaborate on code and reviews, and provide data narrative.

Model Development and Execution: As needed, monitor model performance and retraining efforts.

Communication: Share findings and thoughts on various data science activities with other members of the data science and decision science teams.

Carry out additional responsibilities as assigned by the manager

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Disney Entertainment & ESPN Technology

San Francisco, CA

Required Qualifications:

7+ years of analytical experience is required, as well as a Bachelors degree in advanced mathematics, statistics, data science, or a related field of study.

7+ years of expertise in building machine learning models and analyzing data in Python or R

5+ years of experience developing production-level, scalable code (e.g., Python, Scala)

5+ years of experience creating algorithms for production system deployment

In-depth knowledge of contemporary machine learning algorithms (such as deep learning), models, and their mathematical foundations

Comprehensive knowledge of the most recent natural language processing methods and contextualized word embedding models

Experience building and managing pipelines (AWS, Docker, Airflow) as well as designing big-data solutions with technologies such as Databricks, S3, and Spark

Knowledge of data exploration and visualization tools such as Tableau, Looker, and others

Knowledge of statistical principles (for example, hypothesis testing and regression analysis)

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Asurion

Nashville, TN, USA

Qualifications:

Drive a test-and-learn methodology with a Minimum Viable Product (MVP) and push to learn quickly

Candidate must have the ability to find the root cause, describe, and solve difficult problems in confusing settings

Ability to interact and cooperate with people from many departments inside the organization, ranging from operations teammates to product managers and engineers

Excellent communication (written and spoken) and presentation abilities, especially the ability to create and share complex ideas with peers

The candidate must have creative ideas and arent hesitant to roll up your sleeves to get the job done

Requires a masters degree in analytics, computer science, electrical engineering, computer engineering, or a comparable advanced analytical & optimization discipline, as well as an open mind and an open heart

Familiarity with at least one deep learning framework, such as PyTorch or Tensorflow

Deep Learning and/or Machine Learning expertise earned via academic education or any amount of internship/work experience

Statistics, optimization theoretical principles, and/or optimization problem formulation knowledge acquired via academic coursework or any amount of internship/work experience.

Apply here

Read more from the original source:

Explore the List of Data Scientist Openings in the US - Analytics Insight