Data scientists analyze data and extract information to draw conclusions and actionable insights to the benefit of an organization’s decision making. They collect data from a number of sources, analyze it using predictive analytics, data mining, pattern recognition, machine learning, and data modelling.
They might even (often with help from a data engineer) built AI & machine learning tools to automate business processes.
View the free example Data Scientist job description template below.
Data Scientist Job Description Template
Our growing company is looking to hire an experienced data scientist. You will be in charge of consuming & interpreting vast amounts of data to draw helpful conclusions and build useful systems to solve problems and improve business performance. You will be applying data mining techniques, analyzing data from multiple sources including third parties, and building automated systems to increase efficiency and performance.
Successful candidates must have a strong understanding of machine learning and extensive experience with data science toolkits. You should be proficient in at least one programming language, one scripting language, and one database language. Strong written and verbal communication skills are required to report findings to a non-technical audience.
Data Scientist Responsibilities
- Implementing and validating predictive and prescriptive models
- Using machine learning techniques to select features, build, and optimize classifiers
- Data mining
- Identifying & reporting on business issues (i.e gap analysis)
- Enhancing data collection to include data relevant to building analytical systems
- Manipulating data from a number of sources, both from the company and third parties, using advanced data engineering techniques
- Applying advanced analytic techniques such as recommendation systems, statistics, deep learning, algorithms, and mathematical models
- Processing, cleansing, and verifying data integrity before analysis
- Presenting results clearly and reporting on findings, both verbally and in written format, to a non-technical audience
- Creating automated detection systems for anomalies to prevent future issues
- Tracking the performance of automated systems
- Extending company data with information sourced from third parties
- Conducting ad-hoc analysis
- Researching and developing deep learning models as a solution to business problems
- Implementing new methodologies as needed
- Building out reporting dashboards and pipelines for organization-wide consumption
Data Scientist Requirements
- Bachelors or Masters degree in computer science, data science, statistics, economics, finance, mathematics, engineering, or other quantitative field.
- 2+ years of relevant experience.
- Experience in leveraging data to drive a significant business impact.
- Data-oriented personality.
- Good applied statistics skills, including distributions, statistical testing, regression, time series forecasting, mixed model, clustering, and Bayesian methods.
- Experience with data visualization tools (D3.js, GGplot).
- Great written and verbal communication skills.
- Experience with full cycle machine learning implementation.
- Extensive experience with common data science toolkits (R, Weka, NumPy, MatLab).
- Strong comprehension of machine learning techniques (TensorFlow, Keras, ScikitLearn, H20.ai, MXNet, Caffe, Gluon).
- Experience with machine learning algorithms such as regression, neural networks, and clustering (k-NN, Naive Bayes, SVM, Decision Forests).
- Proficiency in using query languages (SQL, Hive, Pig).
- Experience in developing, tuning, and debugging complex SQL applications.
- Experience working with Big Data and NoSQL databases (MongoDB, Cassandra, HBase, Snowflake, Hadoop, Spark).
- Good scripting and programming skills.
- Experience in feature extraction.
- Experience with programming in languages such as Python, Java, Scala, Ruby, R.
- Pattern recognition and predictive modeling skills.
- Experience in real-time analytics development and deployment.
- Extensive experience in data mining, segmentation, and statistical analysis.
- Able to understand various data structures and common data transformation methods.
- Strong attention to detail and accuracy.
- An understanding of statistical measures such as confidence intervals, development and evaluation data sets, significance of error measurements.
Data Scientist FAQ
Can I customize the data scientist job description?
You can edit our sample data scientist job description as needed. Update the duties, responsibilities, and requirements above to reflect the skills and traits required by your company.
What information should I include in a job posting for a data scientist?
Use our template to start, and add any additional requirements or duties that are specific to what your company will need from a candidate. Make additions such as “develop internal A/B testing procedures,” “build recommendation systems,” or “build an automated lead scoring system,” to get the job description that matches what your company will require from a data scientist.
What are some interview questions for data scientists?
We have sample interview questions for all of our job descriptions.
After you have created a data scientist job posting that suits your company, have a look at our data scientist interview questions.