Data Analyst

3 weeks ago

San Francisco, California, United States Unreal Gigs Full time
Job Title: Data Scientist

Company Overview:

At Unreal Gigs, we're at the forefront of data science innovation. Our mission is to develop cutting-edge data science solutions that unlock the potential of data and drive business success.

Position Overview:

As a Data Scientist, you'll play a pivotal role in transforming data into actionable insights and driving data-driven decision-making across our organization. You'll work closely with cross-functional teams to leverage advanced analytical techniques and machine learning algorithms to solve complex business problems and uncover valuable insights from data.

Key Responsibilities:

  1. Data Exploration and Preparation: Explore and analyze complex datasets to understand data patterns, trends, and relationships, and prepare data for analysis and modeling.
  2. Predictive Modeling: Develop and deploy predictive models using machine learning algorithms to solve business problems such as customer churn prediction, demand forecasting, and fraud detection.
  3. Statistical Analysis: Apply statistical techniques to analyze data, test hypotheses, and derive actionable insights that drive business decisions and strategies.
  4. Data Visualization: Create compelling visualizations and dashboards to communicate insights and findings to stakeholders, using tools such as Tableau, Power BI, or matplotlib.
  5. Feature Engineering: Engineer features from raw data to improve model performance and accuracy, using techniques such as dimensionality reduction, feature scaling, and feature selection.
  6. Model Evaluation and Validation: Evaluate and validate the performance of predictive models using appropriate metrics and techniques, and iterate on model development to improve performance.
  7. Model Deployment: Deploy models into production environments and integrate them into operational systems to enable real-time decision-making and automation.
  8. Collaboration and Communication: Collaborate with cross-functional teams to understand business requirements, translate them into data science solutions, and communicate findings and recommendations to non-technical stakeholders.

Qualifications:

  • Master's degree or higher in Computer Science, Statistics, Mathematics, or related field.
  • Strong background in statistics, mathematics, and machine learning, with hands-on experience in applying advanced analytical techniques to real-world problems.
  • Proficiency in programming languages such as Python or R, and experience with data manipulation and analysis libraries such as pandas, NumPy, and scikit-learn.
  • Experience with machine learning techniques such as classification, regression, clustering, time series analysis, and natural language processing.
  • Familiarity with data visualization tools and techniques for creating interactive visualizations and dashboards.
  • Strong problem-solving abilities and analytical thinking, with a passion for tackling complex data science challenges and driving actionable insights.
  • Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.

Benefits:

  • Competitive salary: The industry standard salary for Data Scientists typically ranges from $140,000 to $210,000 per year, depending on experience and qualifications.
  • Comprehensive health, dental, and vision insurance plans.
  • Flexible work hours and remote work options.
  • Generous vacation and paid time off.
  • Professional development opportunities, including access to training programs, conferences, and workshops.
  • State-of-the-art technology environment with access to cutting-edge tools and resources.
  • Vibrant and inclusive company culture with team-building activities and social events.
  • Opportunities for career growth and advancement within the company.
  • Exciting projects with real-world impact across diverse industries.
  • Chance to work alongside top talent and industry experts in the field of data science.

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