Data Scientist I identifies business trends and problems through complex big data analysis. Interprets results from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining independently. Being a Data Scientist I designs, develops and implements the most valuable business solutions for the organization. Prepares big data, implements data models and develops database to support the business solutions. Additionally, Data Scientist I may require an advanced degree. Typically reports to a manager. The Data Scientist I work is closely managed. Works on projects/matters of limited complexity in a support role. To be a Data Scientist I typically requires 0-2 years of related experience.
Data Scientist Job Description Template
Our company is looking for a Data Scientist to join our team.
Responsibilities:
- Assess the effectiveness and accuracy of new data sources and data gathering techniques;
- Use predictive modelling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes;
- Coordinate with different functional teams to implement models and monitor outcomes;
- Develop custom data models and algorithms to apply to data sets;
- Identify success metrics and monitor them to ensure high-quality output for the client;
- Doing ad-hoc analysis and presenting results in a clear manner;
- Processing, cleansing, and verifying the integrity of data used for analysis;
- Propose solutions and strategies to business challenges;
- Identify and evangelize new and upcoming analytical trends in the market within the organization;
- Enhancing data collection procedures to include information that is relevant for building analytic systems;
- A good team player who has to work together with our machine learning experts, engineers and project managers to advance our data science products;
- Deliver production-ready models that can be deployed in the production system;
- Work in an agile team with emphasis on quality, testability, and automation;
- Data mining using state-of-the-art methods;
- Overall project management – Creating a project plan and timelines for the project and obtain sign-off.
Requirements:
- Strong oral and written communication skills;
- Exposure to NLP technologies and analyses;
- Experience working across multiple compute environments to create workflows and pipelines (e.g. HPC, cloud, Linux systems);
- Bachelor’s Degree in a quantitative discipline (Economics, Engineering, Computer Science, Math, Statistics);
- Out-of-box Problem Solving;
- A drive to learn and master new technologies and techniques;
- Experience with various sdks like mitie, dib, stanford NLP, etc are preferred;
- Good applied statistics skills, such as distributions, statistical testing, regression, etc;
- Strong problem-solving skills with an emphasis on product development;
- Strong verbal and written communication skills with other developers and business client;
- Identify actionable insights that directly address challenges / opportunities;
- Experience developing scalable machine learning solutions within a distributed computation framework (e.g. Hadoop, Spark);
- Combination of the technologies you should be familiar with Kafka, Storm, Logstash, ElasticSearch, Hadoop, Spark;
- Fluency in python with working knowledge of ML & Statistical libraries (e.g. scikit-learn, pandas);
- 1-2 years experience in analytics or management consulting.