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Data Scientist (TX)

  • Permanent
  • Anywhere

Website Tiger Analytics

Tiger Analytics

Company : Tiger Analytics

Country: United States

Location : Houston, Texas

Post: Tue, 27 Sep 2022 11:24:31 GMT

Expires: Tue, 25 Oct 2022 23:59:59 GMT

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—————————— Job Description ——————————

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

As a Data Scientist, you will apply strong expertise in AI through the use of machine learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Key Responsibilities

Extract and manipulate data using a combination of different tools including SQL, Python etc.

Build machine learning/statistical models and perform analysis. Uncover insights and build strategic recommendations that support objectives for business

Solve complex problems using advanced mathematical modeling and optimization techniques, including but not limited to, big data pre-processing, problem formulation, features engineering, algorithmic selection and evaluation, hyper-parameter tuning for machine learning, and deployment.

Actively identify and implement initiatives to improve data extraction, data preparation and data modeling processes

Continuously evaluate ML models and processes and offer solutions to ensure they are efficient, high-quality, and scalable

Build high-quality reusable code that can be used as a framework and can be shared throughout the firm

Contribute on all the stages of data science projects: from performing raw data mining to translating complex technical topics into business solutions

Maintains and enhances a set of critical ML models supporting several use cases

Maintains complex data pipeline supporting our team’s mission in democratizing data and enabling a data-driven organization, partnering with business and IT teams

Effectively communicate actionable insights at all levels of the organization

Collaborate closely with leadership, engineering, and other stakeholders to improve the client’s view of modeling and decision engines

Present compelling data stories to the internal and external teams

Requirements

4+ years of ML/AI model development experience

Strong in SQL, ML libraries and frameworks

Proficiency in programming languages including, Python

Hands on experience in an analytical field of study (e.g. Statistics, Computer Science, Engineering, Mathematics, Finance)

Demonstrated success working with large data sets and analytic tools. Data mining experience working with a large relational database is an asset

Previous work in a cloud-based service such as Azure, or AWS is an asset

Working knowledge of machine learning techniques

Superb analytical and conceptual thinking skills; to not only manipulate but also derive meaningful interpretations from data

Ability to take initiative, multi-task and work in a fast-paced environment

A team player and self-starter

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

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