What are the responsibilities and job description for the Data Scientist (hybrid/onsite) position at System One?
Data Scientist
Washington, DC – hybrid/onsite
6-12 month contract
Technical Skills:
Programming:
• Proficiency in Python and R is crucial. These languages are the workhorses of data science.
• Strong SQL skills for database management and data retrieval.
• Familiarity with other languages like Scala or Java for big data processing can be beneficial.
Statistical Analysis and Mathematics:
• A solid understanding of statistical concepts like probability, hypothesis testing, and regression analysis.
• Knowledge of linear algebra, calculus, and other mathematical foundations.
• Ability to apply statistical methods to extract meaningful insights from data.
Machine Learning and Artificial Intelligence (AI):
• Expertise in various machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning).
• Deep learning knowledge for complex tasks like image and natural language processing.
• Experience with machine learning frameworks like scikit-learn, TensorFlow, and PyTorch.
Data Wrangling and Database Management:
• Ability to clean, preprocess, and transform data from various sources.
• Experience with database systems (e.g., relational, NoSQL).
• Proficiency in data manipulation tools and techniques.
Data Visualization:
• Ability to create clear and compelling visualizations using tools like Matplotlib, Seaborn, and Tableau.
• Skill in communicating data insights effectively through visual representations.
Big Data Technologies:
• Familiarity with big data platforms like Hadoop and Spark. (optional)
• (essential)Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud).
Natural Language Processing (NLP):
• Understanding of NLP techniques for text analysis, sentiment analysis, and language modeling.
Soft Skills:
Problem-Solving:
• Ability to define problems, develop solutions, and implement them effectively.
• Strong analytical and critical thinking skills.
Communication:
• Ability to communicate complex technical concepts to both technical and non-technical audiences.
• Strong presentation and storytelling skills.
Business Acumen:
• Understanding of business objectives and the ability to translate data insights into actionable strategies.
• Ability to identify opportunities for data-driven innovation.
Collaboration:
• Ability to work effectively in teams and collaborate with stakeholders from different departments.
• Adaptability and a willingness to learn.
In essence, we need a very capable data scientist that possesses a strong blend of technical expertise and soft skills, enabling them to extract valuable insights from data and drive meaningful business outcomes. Big plus if they have worked with non-profit, large trade organizations or non-profit and (kina of a reach) knows something about the build industry – architecture, design, etc.
#M2
Ref: #850-Rockville (ALTA IT)
Washington, DC – hybrid/onsite
6-12 month contract
Technical Skills:
Programming:
• Proficiency in Python and R is crucial. These languages are the workhorses of data science.
• Strong SQL skills for database management and data retrieval.
• Familiarity with other languages like Scala or Java for big data processing can be beneficial.
Statistical Analysis and Mathematics:
• A solid understanding of statistical concepts like probability, hypothesis testing, and regression analysis.
• Knowledge of linear algebra, calculus, and other mathematical foundations.
• Ability to apply statistical methods to extract meaningful insights from data.
Machine Learning and Artificial Intelligence (AI):
• Expertise in various machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning).
• Deep learning knowledge for complex tasks like image and natural language processing.
• Experience with machine learning frameworks like scikit-learn, TensorFlow, and PyTorch.
Data Wrangling and Database Management:
• Ability to clean, preprocess, and transform data from various sources.
• Experience with database systems (e.g., relational, NoSQL).
• Proficiency in data manipulation tools and techniques.
Data Visualization:
• Ability to create clear and compelling visualizations using tools like Matplotlib, Seaborn, and Tableau.
• Skill in communicating data insights effectively through visual representations.
Big Data Technologies:
• Familiarity with big data platforms like Hadoop and Spark. (optional)
• (essential)Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud).
Natural Language Processing (NLP):
• Understanding of NLP techniques for text analysis, sentiment analysis, and language modeling.
Soft Skills:
Problem-Solving:
• Ability to define problems, develop solutions, and implement them effectively.
• Strong analytical and critical thinking skills.
Communication:
• Ability to communicate complex technical concepts to both technical and non-technical audiences.
• Strong presentation and storytelling skills.
Business Acumen:
• Understanding of business objectives and the ability to translate data insights into actionable strategies.
• Ability to identify opportunities for data-driven innovation.
Collaboration:
• Ability to work effectively in teams and collaborate with stakeholders from different departments.
• Adaptability and a willingness to learn.
In essence, we need a very capable data scientist that possesses a strong blend of technical expertise and soft skills, enabling them to extract valuable insights from data and drive meaningful business outcomes. Big plus if they have worked with non-profit, large trade organizations or non-profit and (kina of a reach) knows something about the build industry – architecture, design, etc.
#M2
Ref: #850-Rockville (ALTA IT)
