Data Scientist

Data Scientist

Location: Plano, TX (Hybrid)

Duration: 12+ Months Contract

Who we’re looking for:

Strong experience manipulating data set and building statistical models, has master’s or Ph.D. in statistics, mathematics with focus on ML, NLP, machine learning or another quantitative field.

Strong knowledge and experience in statistical and data mining techniques – GLM/regression, Random Forest, Boosting, text and data mining.

Experience querying database and using statistical computer languages: R, Python, SQL etc.

Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.

Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc.

Experience visualizing/presenting data for stakeholders using: Tableau, Business Objects, D3

Exp with Prescriptive analysis, predictive analysis.

Exp leveraging big data and search technologies (e.g., Spark, Elastic Search, Natural Language Processing, Web Crawling).

Knowledge of machine learning techniques and algorithms and be able to apply them in data driven natural language processing techniques.

Ability to quickly prototype ideas / solutions and perform critical analysis and using creative approaches for solving complex problems.

Exp with Automotive analytics a PLUS

Excellent written and verbal communication skills

What you will do:

This role is a hands-on data scientist to work very closely with business stakeholders helping to analyze the data and suggested patterns and models to help them improve their business outcomes.

Serve as lead data strategist to identify and integrate new datasets that can be leveraged through our product capabilities, and work closely with the engineering team in the development of data products.

Execute analytical experiments to help solve problems across Automobile Domain

Identify relevant data sources and sets to mine for client business needs and collect large structured and unstructured datasets and variables.

Devise and utilize algorithms and models to mine big-data stores; perform data and error analysis to improve models; clean and validate data for uniformity and accuracy.

Analyze data for trends and patterns and interpret data with clear objectives in mind.

Implement analytical models in production by collaborating with software developers and machine-learning engineers.

Work closely with business stakeholders, Software engineering team and data team to deliver the required outcomes.