SUMMARY:

Our client, a hyper growth PE firm based in Houston is seeking a Data Scientist who embodies strategic leadership and a practical, application-oriented mindset. This role is perfect for someone eager to make a substantial business impact utilizing a broad toolbox of data-driven methodologies.

In this position, you will play a vital role in analyzing data across the organization, focusing on technical and deal diligence to enhance the business development of portfolio companies. Your ability to translate complex technical subjects into clear business language will empower stakeholders to make informed decisions. As a project manager, you will lead initiatives to build and integrate innovative digital applications, aligning them with our strategic and sustainable business goals.

Your role goes beyond traditional data science; it's about harnessing the power of data to create tangible business outcomes. Collaborating with a larger offshore team, you will develop solutions that are not just theoretically sound but are pragmatically designed to drive change and deliver real-world results. Reporting to the Head of Data Science, you will establish yourself as a key figure in shaping Quantum’s data-driven future, with a clear focus on practical applications and business impact.

DESCRIPTION:

Able to lead projects and work collaboratively with cross-functional teams, including data engineers, data analysts, and other stakeholders.

Develops modern machine learning, statistical and ensemble methods for finding patterns from business and operational data.

Performs in-depth investigations of exploratory data analysis employing statistical skills.

Uses statistical methods for feature computation, selection, and dimensionality reduction.

Creates effective visualizations for technical, business, and managerial audience.

Delivers data driven insights to understand business KPIs.

Contributes to the company’s digital strategic direction, development, and future growth.

Capable to apply generative AI in innovative ways to solve complex problems, generate new ideas, or create data-driven strategies.

Critical thinking in building and deploying digital solutions.

Effective change leader, skilled at resolving implementation hurdles and motivating adoption across the organization.

Staying up to date with the latest advancements in AI and generative models and understanding how these can be applied within the organization.

Implements standard Machine Learning methodology across eco-system.

Conducts hands on research and case studies on leading edge technologies, advise on technical direction, and provide determination of probability for implementation.

REQUIREMENTS:

Strong quantitative skills in Probability, Statistics, Algorithms, Optimization methods and Machine / Deep Learning models.

Proven track record of delivering business value using AI.

Solid experience in Classical Machine Learning, Deep Learning, Bayesian Learning and Survival Analysis methods.

Experience with advanced generative models like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformer-based models.

Fluency of Machine Learning frameworks such as Scikit-learn, TensorFlow, PyTorch, Keras, PyMC.

Experience with GPU computing and parallel processing would be advantageous.

Good understanding of Natural Language Modeling and experience in Text Analytics.

Good experience in conducting Time Series Analysis.

Have worked on projects related to Prognostic Health Management.

Extensive experience in programming language such as Python, R, Julia, SQL.

Comfortable in building data visualization applications using PowerBI, Spotfire, Bokeh, Plotly.

Worked on querying and storing data in NoSQL databases.

Fluency in big data technologies such as Databricks and cloud Machine Learning frameworks like AzureML.

Strong familiarity with agile software development.

Strong knowledge of MLOps best practices.

Strong communication skills and the ability to effectively discuss models with other data scientists as well as business partners at the appropriate level of technical detail.

Awareness of the ethical implications of AI, particularly in the context of generative models, and commitment to developing responsible AI solutions.

BS, MS / PhD in Computer Science or Applied Science or Engineering Disciplines.

Energy domain expertise in Exploration & Production and/or Energy Transition & Decarbonization a plus.

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Data Scientist