This Lead Data Scientist job description template helps to attract candidates best suited for this position. It gives you a clear picture of the responsibilities and requirements of a Lead Data Scientist and thus makes your hiring process easier. You can customize it and use it to post on online job boards.
Job Brief :
We are looking for a Lead Data Scientist for our organization who can derive value from raw data.
The candidate is responsible for identifying the correct source or quality data collection. You will plan projects and streamline data products according to the company’s goals. Excellent statistical analysis, team management skills and problem-solving abilities are plus points for this job.
To excel in this profession you should have the creativity of handling data and deriving useful values from raw data. Thus contributing remarkably to the growth of the company.
Responsibilities :
- Manage data scientist and data specialist team.
- Identify the efficient source for quality data collection,
- Lead data collection and data mining processes.
- Ensure and guarantee data integrity.
- Analyze data and interpret data problems.
- Plan project, prioritize and streamline all planed data projects.
- Develop a proper analytic system according to the requirements.
- Analyze and test the performance of the products.
- Build reports on the visualization and performance of the products.
- keep implementing new techniques and models.
- Line up the data projects according to the goals of the company.
Requirements :
- Bachelor’s degree in Data Science, Computer Science, or other related fields.
- Proven experience in Data Science and other related fields.
- Good understanding o techniques of data management and visualization.
- Expertise in statistical data analysis and predictive data modeling.
- Good technical and coding knowledge of Python, R language, MATLAB, SQL and other databases.
- Outstanding communication skills.
- Inspiring leadership qualities and organizational skills.
Lead Data Scientist Job Description FAQs:
What is a typical payout for a Lead Data Scientist?
Salaries depend on location and years of experience involved. But on an average a Lead Data Scientist on an entry-level earn about ₹2,200K per year.
How can this Job Description help me broaden my reach for better candidates?
Posting this job description on various job boards such as Adzuna, ZipRecruiter and CareerJet can help get you better reach of the candidates. Using an ATS like Recooty can help save you a great deal of manual work! This allows you to post jobs to more than 20+ job sites on a single click
Which industries lookout for Lead Data Scientist?
-Retail & Ecommerce,
-Medicine,
-Construction,
-Transportation,
-Banking & Finance,
-Education & E-Learning,
-Media & Entertainment,
-Energy,
-Logistic & Transportation,
-Manufacturing,
-Natural resources
are some industries that look out for Lead Data Scientist.
What are the top skills for a Lead Data Scientist?
Top skills for a Lead Data Scientists are :
-Critical Thinking: to be able to deal with critical issues and apply proper objective analysis critical thinking ability is very important.
-Coding: We know that a data scientist has to deal with real-time data, unstructured data, cloud computing, optimization, and various such tasks. To be efficient in accomplishing these tasks good coding skills are important.
-Math: The candidate has to deal with complex financial and operational models. So to develop relevant statistical model expertise in mathematics is essential.
-Problem-solving abilities: Since problem-solving is an important duty in this job post the candidate must be good at it.
-System engineering and risk analysis: To be successful in this job post you must have a good analysis of business risk, process improvement, and system engineering.
-Communication skills: To be able to communicate effectively with various stakeholders using data communication skills are a key point.
-Data architecture: As the data architecture has a wide impact on size inference, etc. Basic idea about Data Architecture is important to achieve get results.
-AI, Machine Learning: The use of Machine Learning and AI is increasing incredibly in the industries today. To have the basic knowledge about it works in your favor.
