Data Scientist - Qualified Pipeline

Data Meaning; United States; Remote; USD 80,000 - 120,000; Full time

Job summary

A leading company in Business Intelligence and Data Analytics consulting is building a pipeline for qualified Data Scientists. This role will involve data analysis, statistical modeling, and the application of machine learning techniques in a collaborative remote work environment.

Qualifications

• At least 4 years of professional experience in a data-related role.
• Good communication skills (English proficiency) required.
• Knowledge of Statistics and Statistical Modeling essential.

Responsibilities

• Analyze large amounts of information to discover trends and patterns.
• Build predictive models and propose solutions for business issues.
• Communicate complex statistical concepts to non-technical audiences.

Skills

Data Analysis

Data Mining

Statistical Modeling

Big Data Infrastructure

Machine Learning

Education

Bachelor’s degree in Computer Science, Math or Statistics

Tools

Python

R

SQL

NoSQL

Power BI

Tableau

Job description

Data Scientist - Qualified Pipeline

• Location: Latam/US
• Position Pay: Salary depends on experience

POSITION SUMMARY:

Data Meaning is a front-runner in Business Intelligence and Data Analytics consulting, renowned for our high-quality consulting services throughout the US and LATAM. Our expertise lies in delivering tailored solutions in Business Intelligence, Data Warehousing, and Project Management. As a Tableau Preferred Partner and the distinguished Alteryx 2020 Global Partner of the Year, we are dedicated to bringing premier services to our diverse clientele. Our strength lies in our global team of 95+ consultants, all working remotely, embodying a collaborative, inclusive, and innovation-driven work culture.

We are proactively building a pipeline for qualified Data Scientists to joinour team in the near future.

The IDEAL candidate will have experience with either Python or R, Power BI or Tableau, and excellent understanding of Data Analysis, Data Mining, Statistic Modeling and Big Data Infrastructure.

RESPONSIBILITIES:

• Follow consistent practices to ensure data integrity and deal with imperfections in data.
• Effectively process structured and semi-structured/unstructured data; proficiently integrate varied datasets
• Work cross-functionally with development and engineering teams
• Analyze large amounts of information to discover trends and patterns, draw conclusions and gain actionable insights.
• Build predictive models; propose solutions and strategies for business problems
• Apply the appropriate machine learning algorithm to data problems (e.g. supervised vs. unsupervised machine learning, clustering, ensemble methods, etc.), validate model results.
• Work closely with architecture and engineering team to deploy models; communicate results in a clear and non-technical manner.
• Interact with senior management and effectively communicate technical information to numerous audiences (e.g. senior management, client community, peers and junior associates)
• Address challenges to analytic processes and influence others to change their approach and work collectively to implement new tools/techniques
• Gain support from related stakeholders for analytic solutions and champion data driven business decisions.
• Apply appropriate statistical techniques to data exploration and model development/assessment
• Communicate complex statistical concepts to non-technical audiences; maintain skills through continuing education.
• Create meaningful data visualizations to communicate results and highlight business impact
• Effectively collaborate with others to deliver efficient and high-quality code (Python or R)
• Implement solid validation process to ensure consistency and minimize errors in code
• Champion more efficient ways to produce code, maintain skills through continuing education; stay up to date on new technologies/ tools
• Seamlessly transition between languages to apply the right approach to the problem.
• Understanding of Big Data infrastructure – Hadoop, MapReduce and Spark

REQUIREMENTS:

• Bachelor’s degree in Computer Science, Math or Statistics is preferred
• At least 4 years of professional experience in a data-related role
• Good communication skills (English proficiency)
• Knowledge of Statistics and Statistical Modeling
• Understanding of Machine Learning and Predictive Analytics
• Data analysis programming languages – Python and R (at least one)
• Database languages – SQL and NoSQL (desirable)
• Data Visualization – Power BI or Tableau