Data Scientist

The Data Scientist will work in teams addressing statistical, machine learning and data understanding problems in a commercial technology and consultancy development environment. In this role, you will contribute to the development and deployment of modern machine learning, operational research, semantic analysis, and statistical methods for finding structure in large data sets.

Essential Responsibilities:

• Develop analytics within well-defined projects to address customer needs and opportunities.
• Work alongside software developers and software engineers to translate algorithms into commercially viable products and services.
• Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.
• Perform exploratory and targeted data analyses using descriptive statistics and other methods.
• Work with data engineers on data quality assessment, data cleansing and data analytics.
• Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
• Share and discuss findings with team members.

Qualifications/Requirements:

• Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with basic experience.

Desired Characteristics:

• Expertise in one or more programming languages and analytic software tools (e.g., Python, R, SAS, SPSS).
• Strong understanding of machine learning algorithms, statistical methods, and data processing techniques.
• Proficiency in applying descriptive, predictive, and prescriptive analytics to solve real-world problems.
• Experience working with big data technologies and tools (e.g., Hadoop, Spark, SQL).
• Excellent communication skills, both written and verbal.
• Commitment to continuous learning and staying up-to-date with the latest advancements in data science and machine learning.
• Ability to thrive in a fast-paced, dynamic environment and adapt to changing priorities.

Technical Expertise:

• Awareness of feature extraction and real-time analytics methods.
• Understanding of analytic prototyping, scaling, and solutions integration.
• Ability to work with large, complex data sets and derive meaningful insights.
• Familiarity with machine learning techniques and their application in solving real-world problems.

Domain Knowledge:

• Demonstrated awareness of industry and technology trends in data science.
• Demonstrated awareness of customer and stakeholder management and business metrics.

Leadership:

• Demonstrated awareness of how to function in a team setting.
• Demonstrated awareness of critical thinking and problem-solving methods.
• Demonstrated awareness of presentation skills.

Personal Attributes:

• Demonstrated awareness of how to leverage curiosity and creativity to drive business impact.
• Humble: respectful, receptive, agile, eager to learn.
• Transparent: shares critical information, speaks with candor, contributes constructively.
• Focused: quick learner, strategically prioritizes work, committed.
• Leadership ability: strong communicator, decision-maker, collaborative.
• Problem solver: analytical-minded, challenges existing processes, critical thinker.