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senior analytics and data solutions specialist Jobs in Houston United States

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associate, digital finance transformation - data scientist - private equity performance improvement (open to all us locations) Jobs in Houston United States

ai computational data scientist

MD Anderson Cancer Center

<div>We seek a talented, energetic, and collaborative AI-driven Data Scientist to develop data science tools and predictive algorithms as part of the development of our flagship platform A3D3a: Adaptive, AI-augmented, Drug Discovery and Development. With expertise in Machine Learning and Deep Learning, the Data Scientist will inform our mission to discover novel therapeutic opportunities for cancer patients. 
 
Led by Prof. Bissan Al-Lazikani, Director of Therapeutics Data Science, the intelligent and ever-learning A3D3a platform is part of MD Anderson's Therapeutics Data Science initiative and part of our ambitious Institute for Data Science in Oncology. A3D3a will accelerate the discovery and impact of novel therapies for cancer by enabling novel opportunities for optimized therapies for patients with a focus on rare and hard-to-treat cancers through the development of novel machine learning and AI technologies. 
 
Central to this vision, the Data Scientist will innovate and deploy Machine Learning and Deep Learning approaches to uncover hidden therapeutic opportunities in integrated patient data and will work closely with biologists, data scientists, and clinicians. 
 
The ideal candidate has strong hands-on experience with machine learning, deep learning, and large language models, and is comfortable using tools like TensorFlow, Keras, and scikit-learn. They can address challenges such as data bias and imbalance, have solid programming skills in Python or similar languages, and possess a strong understanding of statistical methods. This person enjoys solving complex problems and developing practical AI solutions that make a meaningful impact.
 
 
What We Offer? 
<ul><li>Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&amp;D, and disability insurance.</li><li>Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options.</li><li>Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups.</li><li>Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs.</li></ul> 

JOB RESPONSIBILITIES: 
<ul><li>Build data science tools and predictive algorithms focusing on state-of-art machine learning models</li><li>Develop novel deep learning approaches and utilizing Large Language Models and Graph Neural Networks for cancer data</li><li>Maintain knowledge of cutting-edge machine learning approaches and technologies and implement these where appropriate</li><li>Perform data wrangling and preparation for deep learning analysis</li><li>Perform statistical analysis</li><li>Produce output for scientific publications and co-author said publications</li><li>Prepare written reports, manuscripts, and grant applications with investigators</li><li>Attend collaborator meetings and team working group meetings. Prioritize and manage multiple projects in a timely and resource-effective manner.</li><li>Stay up to date with relevant literature, gather information systematically, and confer with the supervisor regarding new procedures.</li><li>Other Duties as assigned.</li></ul> 

EXPECTED SKILLS:
 
<ul><li>Machine Learning (e.g., Na&iuml;ve Bayes, Random Forests, Support Vector Machines, etc.)</li><li>Deep Learning (e.g., Convolutional Neural Networks, Graph Neural Networks, Autoencoders, etc.)</li><li>LLM (fine-tuning, multi-agents)</li><li>Addressing challenges in Machine Learning / Deep Learning as well as mitigation strategies including data bias, imbalance, and model validation approaches</li><li>Machine-learning platforms (e.g., TensorFlow, sklearn, Keras, etc.)</li><li>Unix, Python, R/Matlab, or other scripting/programming languages</li><li>Excellent working knowledge of statistical methods and tests</li></ul> 

EDUCATION: 
Required: Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. 
Preferred: Master's or PhD in Science, Engineering or related field. 
 
EXPERIENCE: 
Required: Three years scientific software or industry development/analysis experience. With Master's degree one year. With PhD, no experience required. 
Preferred: Machine Learning, Large language model, AI Agent and/or Biomedical Research is a plus.
 
 
The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition. 
 
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment. 
 
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html 
 
Additional Information
 
<ul><li>Requisition ID: 179340
</li><li>Employment Status: Full-Time
</li><li>Employee Status: Regular
</li><li>Work Week: Days
</li><li>Minimum Salary: US Dollar (USD) 106,500
</li><li>Midpoint Salary: US Dollar (USD) 133,000
</li><li>Maximum Salary : US Dollar (USD) 159,500
</li><li>FLSA: exempt and not eligible for overtime pay
</li><li>Fund Type: Soft
</li><li>Work Location: Hybrid Onsite/Remote
</li><li>Pivotal Position: Yes
</li><li>Referral Bonus Available?: Yes
</li><li>Relocation Assistance Available?: Yes
</li></ul> 
#LI-Hybrid</div>

AI Computational Data Scientist

<div>We seek a talented, energetic, and collaborative Molecular Modeling Scientist to conduct both routine and novel analyses as part of our flagship platform A3D3a: Adaptive, AI-augmented, Drug Discovery and Development. With experience in structural prediction, comparative modeling, and emerging generative models, the Molecular Modeling Scientist will contribute to the discovery of novel cancer therapeutics as part of A3D3a. 
 
Led by Prof. Bissan Al-Lazikani, Director of Therapeutics Data Science, the intelligent and ever-learning A3D3a platform is part of MD Anderson's Therapeutics Data Science initiative and part of our ambitious Institute for Data Science in Oncology. A3D3a will accelerate the discovery and impact of novel therapies for cancer by enabling novel opportunities for optimized therapies for patients with a focus on rare and hard-to-treat cancers through the development of novel machine learning and AI technologies. 
 
Central to this vision, the Molecular Modeling Scientist will leverage state-of-the-art macromolecular modeling techniques and, collaboratively with senior scientists, develop innovative data science approaches to answer structural questions about and nominate therapeutic targets. Additionally, physics-based modeling may also compliment structural informatics and generative AI efforts. The preferred candidate should have at least an MSc in Chemistry, Biochemistry, Computer Science, or a related field. A strong background in computational modeling and a willingness to learn new approaches is critical to this role. 
 
The ideal candidate will be an experienced computational scientist with strong Python-based scientific computing skills and expertise in cheminformatics, generative AI, and molecular modeling-capable of building predictive ML models, generating and analyzing macromolecular structures, leveraging tools such as PyTorch, Modeller, Rosetta, and MD packages, and contributing effectively to multidisciplinary research through rigorous documentation, scientific communication, and efficient project management.
 
 
JOB RESPONSIBILITIES:
 
<ul><li>Generate comparative macromolecular models of potential therapeutic targets</li><li>Build and apply machine/deep learning models to predict structural properties</li><li>Analyze ensembles of structures through techniques such as clustering</li><li>Document work thoroughly</li><li>Produce output for scientific publications and contribute to said publications</li><li>Present results at multidisciplinary project meetings as well as external meetings</li><li>Attend collaborator meetings and team working group meetings. Prioritize and manage multiple projects in a timely and resource-effective manner.</li><li>Stay up to date with relevant literature, gather information systematically, and confer with the supervisor regarding new procedures.
</li><li>Expertise in scientific computing using Python in a Unix environment</li><li>Proficient with generative AI for structure prediction; familiar with PyTorch.</li><li>Proficiency with Modeller, Rosetta, or other classical comparative modeling tools</li><li>Experience with OpenMM, AMBER, or comparable MD tools</li><li>Experience with molecular visualization tools (i.e., PyMol, VMD)</li><li>Familiar with basic statistical testing</li></ul> 
Other duties as assigned. 
 
EDUCATION:
 
Required: Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. 
Preferred: Master's or PhD Degree Science, Engineering or related field. 
 
EXPERIENCE: 
Required: Three years scientific software or industry development/analysis experience. With Master's degree, one year. With PhD, no experience required. 
Preferred: Proficent with PyTorch. Profient with comparative modeling tools. 
 
The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition. 
 
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment. 
 
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html 
 
Additional Information
 
<ul><li>Requisition ID: 179242
</li><li>Employment Status: Full-Time
</li><li>Employee Status: Regular
</li><li>Work Week: Days
</li><li>Minimum Salary: US Dollar (USD) 106,500
</li><li>Midpoint Salary: US Dollar (USD) 133,000
</li><li>Maximum Salary : US Dollar (USD) 159,500
</li><li>FLSA: exempt and not eligible for overtime pay
</li><li>Fund Type: Soft
</li><li>Work Location: Hybrid Onsite/Remote
</li><li>Pivotal Position: Yes
</li><li>Referral Bonus Available?: Yes
</li><li>Relocation Assistance Available?: Yes
</li></ul> 
#LI-Hybrid</div>

Data Scientist Molecular Modeling

<div>We seek a talented, energetic, and collaborative AI-driven Computational Chemist to conduct both routine and novel analyses as part of our flagship platform A3D3a: Adaptive, AI-augmented, Drug Discovery and Development. With experience in molecular generation, foundation models, and QSAR/QSPR modeling, the AI Computational Chemist will contribute to the discovery of novel cancer therapeutics as part of A3D3a. 
 
Led by Prof. Bissan Al-Lazikani, Director of Therapeutics Data Science, the intelligent and ever-learning A3D3a platform is part of MD Anderson's Therapeutics Data Science initiative and part of our ambitious Institute for Data Science in Oncology. A3D3a will accelerate the discovery and impact of novel therapies for cancer by enabling novel opportunities for optimized therapies for patients with a focus on rare and hard-to-treat cancers through the development of novel machine learning and AI technologies. 
 
Central to this vision, the AI Computational Chemist will leverage state-of-the-art generative and foundation models and, collaboratively with senior scientists, develop innovative data science approaches to propose chemical matter, propose drug-target interactions of on- and off-target effects, and rationalize toxicity patterns. While physics- or docking-based approaches may complement work in this position, proficiency in AI/ML based computational chemistry and cheminformatics is a must. The preferred candidate should have at least a MSc in Chemistry, Biochemistry, Computer Science, or a related field. Expertise and comfortability with large data and a willingness to learn new approaches is critical to this role. 
 
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The ideal candidate will leverage advanced generative chemistry and AI/ML techniques using frameworks such as PyTorch, predict drug-target interactions, and drive data-informed discovery, while bringing strong computational chemistry expertise, large-scale data fluency, and a collaborative, innovation-focused mindset.
 
 
JOB RESPONSIBILITIES: 
<ul><li>Apply generative models to propose chemical matter for targets of interest.</li><li>Develop novel methods in coordination with senior scientists.</li><li>Develop QSAR/QSPR models from public and internal data.</li><li>Document work thoroughly.</li><li>Produce output for scientific publications and contribute to said publications.</li><li>Present results at multidisciplinary project meetings as well as external meetings.</li><li>Attend collaborator meetings and team working group meetings. Prioritize and manage multiple projects in a timely and resource-effective manner.</li><li>Stay up to date with relevant literature, gather information systematically, and confer with the supervisor regarding new procedures.</li><li>Expertise in scientific computing using Python in a Unix environment, plus GPU computing.</li><li>Proficient with generative AI for molecular generation.</li><li>Proficient in PyTorch, rdkit, and other machine/deep learning utilities for cheminformatics.</li><li>Familiar programmatically accessing public databases such as ChEMBL.</li><li>Experience with molecular visualization tools (i.e., PyMol, VMD).</li><li>Familiar with basic statistical testing.</li><li>Other duties as assigned.</li></ul> 

EDUCATION: 
Required: Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. 
Preferred: Master's Degree or PhD in chemistry, structural biology, biochemist, or related field. 
 
EXPERIENCE: 
Required: Three years Scientific software or industry development/analysis experience. With master's degree one year experience. With PhD, no experience.
 
Preferred: Extensive experience with PyTorch. rdKit is a plus. 
 
The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition. 
 
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment. 
 
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html 
 
Additional Information
 
<ul><li>Requisition ID: 179239
</li><li>Employment Status: Full-Time
</li><li>Employee Status: Regular
</li><li>Work Week: Days
</li><li>Minimum Salary: US Dollar (USD) 106,500
</li><li>Midpoint Salary: US Dollar (USD) 133,000
</li><li>Maximum Salary : US Dollar (USD) 159,500
</li><li>FLSA: exempt and not eligible for overtime pay
</li><li>Fund Type: Soft
</li><li>Work Location: Hybrid Onsite/Remote
</li><li>Pivotal Position: Yes
</li><li>Referral Bonus Available?: Yes
</li><li>Relocation Assistance Available?: Yes
</li></ul> 
#LI-Hybrid</div>

Data Scientist Generative Chemistry

YO IT Consulting

<div>
 Contract
 
 
 Remote
 
 
 Role Description
 
 
 As a remote, hourly paid R Engineer, you will review AI-generated responses and generate high-quality R and data-analysis-focused content, evaluating the reasoning quality and step-by-step problem-solving behind each solution. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in statistical methodology or data-wrangling workflows; fact-check analytical results; write expert-level explanations and model solutions that demonstrate correct use of R; and rate and compare multiple AI responses based on correctness and reasoning quality. This contract role is with, a fast-growing AI Data Services company and subsidiary of that provides AI training data for many of the world&rsquo;s largest AI companies and foundation model labs, directly helping to improve the world&rsquo;s premier AI models.
 
 
 Your Profile
 
 
 <ul>
 <li>
 2+ years of hands-on experience using R for data analysis, statistics, or data science work.
 </li>
 <li>
 Strong proficiency in R programming, including data wrangling, functional programming patterns, and writing reusable functions or packages.
 </li>
 <li>
 Solid grounding in applied statistics, including regression, inference, and model validation, with practical experience implementing these methods in R.
 </li>
 <li>
 Experience building end-to-end analyses in R that include data cleaning, exploratory analysis, modeling, and visualization.
 </li>
 <li>
 Familiarity with common R ecosystems such as tidyverse, data.table, and ggplot2, and the ability to choose appropriate tools for a given task.
 </li>
 <li>
 Professional experience in a data-focused role such as data scientist, statistician, quantitative analyst, or similar.
 </li>
 <li>
 Minimum Bachelor&rsquo;s degree in Statistics, Mathematics, Computer Science, or a closely related quantitative field.
 </li>
 <li>
 Significant experience using large language models (LLMs) to assist with coding, analysis design, and code review in R.
 </li>
 <li>
 Excellent English writing skills with the ability to document analyses and explain complex statistical ideas clearly to non-experts.
 </li>
 <li>
 Previous experience with AI data training or model evaluation is strongly preferred, and Minimum C1 English proficiency is required.
 
 
 </li>
 </ul>
 Key Responsibilities
 
 
 <ul>
 <li>
 Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
 </li>
 <li>
 Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
 </li>
 <li>
 Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.
 </li>
 </ul>
</div>

R - Programming Software Engineer

Andiamo

<div>
 Senior Machine Learning Scientist, Foundation Models for Time Series and Sensors
 
 
 We are looking for a Machine Learning Scientist who is excited by the challenge of teaching machines to understand the physical world through data. This role focuses on building large scale foundation models that learn deep representations from time series, sequential sensor streams, and other complex signals, with direct application to industrial, scientific, and real world systems.
 
 
 
 About The Role
 
 
 
 In this position, you will design, train, and deploy self supervised and semi supervised learning systems that operate across time series, sensor data, vision, and text. Your work will enable advanced capabilities such as anomaly and event detection, predictive maintenance, forecasting, classification, and sensor fusion. You will help define the next generation of intelligent systems that operate reliably in noisy, high consequence environments.
 
 
 What You Will Work On
 
 
 <ul>
 <li>
 Develop large scale foundation models that learn transferable representations from sequential and sensor based data
 </li>
 <li>
 Apply self supervised learning techniques to unlock value from unlabeled and weakly labeled datasets
 </li>
 <li>
 Fine tune and adapt pretrained models for specialized downstream tasks across industrial and scientific domains
 </li>
 <li>
 Design systems that combine time series, images, audio, text, and structured data into unified learning architectures
 </li>
 <li>
 Collaborate with domain experts to ensure models align with real world constraints and objectives
 
 
 </li>
 </ul>
 Data and Signal Processing Expertise
 
 
 <ul>
 <li>
 Process and analyze univariate and multivariate time series from domains such as industrial systems, IoT, finance, healthcare, or scientific instrumentation
 </li>
 <li>
 Perform data augmentation, feature extraction, resampling, and noise handling for real world sensor streams
 </li>
 <li>
 Work with diverse sensor modalities including vibration, temperature, accelerometers, audio, imagery, and more
 </li>
 <li>
 Handle synchronization challenges, variable sampling rates, and imperfect data collected in operational environments
 
 
 </li>
 </ul>
 Machine Learning and Model Development
 
 
 <ul>
 <li>
 Build models using sequence focused architectures such as recurrent networks, temporal convolutional networks, and transformer based systems
 </li>
 <li>
 Apply contrastive learning, masked prediction, temporal forecasting objectives, and multimodal alignment techniques
 </li>
 <li>
 Leverage transfer learning, adapter based methods, and few shot strategies for efficient adaptation
 </li>
 <li>
 Evaluate models using both technical metrics and end user or business driven performance indicators
 
 
 </li>
 </ul>
 Software and Training Infrastructure
 
 
 <ul>
 <li>
 Develop high performance pipelines in Python using scientific and data libraries
 </li>
 <li>
 Optimize components with C++ or CUDA when needed for large scale preprocessing or training
 </li>
 <li>
 Train models using modern deep learning frameworks such as PyTorch, TensorFlow, or JAX
 </li>
 <li>
 Scale training across multiple GPUs and nodes using distributed and mixed precision techniques
 </li>
 <li>
 Build reliable data pipelines for ingesting, cleaning, segmenting, and aligning massive sensor datasets
 
 
 </li>
 </ul>
 Mathematical and Algorithmic Foundations
 
 
 <ul>
 <li>
 Strong grounding in linear algebra, probability, statistics, and optimization
 </li>
 <li>
 Experience with signal processing methods such as Fourier analysis, wavelets, filtering, and time frequency techniques
 </li>
 <li>
 Familiarity with numerical methods for modeling dynamic systems and solving inverse problems
 
 
 </li>
 </ul>
 Collaboration and Communication
 
 
 <ul>
 <li>
 Work closely with engineers, researchers, product leaders, and end users from technical and non technical backgrounds
 </li>
 <li>
 Clearly explain model behavior, uncertainty, and tradeoffs to diverse audiences
 </li>
 <li>
 Contribute to documentation, design discussions, and technical decision making
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 MS or PhD in Computer Science, Artificial Intelligence, Data Science, or a closely related field
 </li>
 <li>
 Three or more years of hands on experience in machine learning, data science, or applied AI
 
 
 </li>
 </ul>
 This role offers the opportunity to work at the frontier of foundation models for time series and sensor data, solving problems that matter in the physical world and shaping systems that operate at scale in complex, real environments.
 
 
 
 About Andiamo
 
 
 
 Talent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world&rsquo;s largest and most well-known companies.
 
 
 For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.
 
 
 Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com
</div>

Data Scientist - Drilling - Global Energy Tech Company

Baylor College of Medicine

<div><div><div><div><h2 class="jobSectionHeader">Summary</h2></div><div>
Biostatistician will support diverse clinical research initiatives across the department. This role involves designing and analyzing studies using advanced biostatistical methods, collaborating with investigators, and interpreting complex datasets to for research and clinical care. The Biostatistician will also contribute to the development and review of study protocols, manuscripts, and computational programs, while providing statistical expertise for research grant applications. 
 
This position will support a wide range of research projects across the Department of Pediatrics and Texas Children's Hospital. It will require knowledge and expertise in a wide range of standard and advanced biostatistical techniques and experience with major common software packages. It will not suffice to have experience only with bioinformatics or informatics platforms.</div></div><div><div><h2 class="jobSectionHeader">
Job Duties</h2></div><div><ul><li>
Meets with faculty, trainees, and staff to understand the statistical needs of research projects.</li><li>
Collaborates with biostatistics faculty and team members to develop data analysis plans.</li><li>
Uses statistical software to create programs for data management, manipulation, and standard/advanced analysis.</li><li>
Performs statistical analyses in accordance with established data analysis plans.</li><li>
Provides and interprets reports detailing statistical methodology, results, and data interpretation.</li><li>
Contributes to the writing and review of study protocols, manuscripts, and computational programs.</li><li>
Effectively interacts with investigators and presents statistical methods and results.</li><li>
Assists and trains faculty, trainees, and staff in the use of software for data management and analysis.</li><li>
Communicates and presents statistical reports, findings, and methodologies to investigators and department leadership.</li><li>
Provides regular timelines and project updates to the Center Director, as requested.</li><li>
Prepares reports documenting research activities and results for Department administration.</li><li>
Collaborates with data managers and information services specialists at Texas Children's Hospital to request health data for clinical research projects.</li><li>
Performs other job-related duties as assigned by biostatistics faculty.</li></ul></div></div><div><div><h2 class="jobSectionHeader">
Minimum Qualifications</h2></div><div><ul><li>
Bachelor's degree in Statistics, Biostatistics or a related field.
</li><li>Two years of relevant experience.</li></ul></div></div><div><div><h2 class="jobSectionHeader">
Preferred Qualifications</h2></div><div><ul><li>
Master's degree in a related field.</li><li>
Knowledge and expertise in a wide range of standard and advanced biostatistical techniques.</li><li>
Experience with major common software packages.</li></ul></div></div></div> 
Work Authorization Requirement:
This position is not eligible for visa sponsorship. Candidates must be legally authorized to work in the United States at the time of application and throughout the duration of employment. 
Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.</div>

Biostatistician

Tiger Analytics

<div>Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants 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.
We are seeking a Data Scientist with strong downstream refining experience to drive data-driven insights across refinery operations, economics, and reliability. This role partners closely with process engineers, operations, planning, maintenance, and commercial teams to optimize refinery performance using advanced analytics, machine learning, and domain-informed modeling.
You&rsquo;ll work on high-impact problems such as yield optimization, energy efficiency, unit reliability, predictive maintenance, and margin improvement&mdash;turning complex refinery data into actionable intelligence.
Analytics &amp; Modeling<ul><li>
Develop, validate, and deploy statistical, ML, and optimization models for refining operations</li><li>
Build models supporting:</li><li><ul><li>
Unit performance optimization (e.g., CDU/VDU, hydrotreating, cracking)</li><li>
Energy efficiency and utilities optimization</li><li>
Yield and cut-point optimization</li><li>
Predictive maintenance and reliability analytics</li><li>
Fouling, corrosion, and anomaly detection</li></ul></li><li><ul><li>
Apply time-series analysis to high-frequency plant data (DCS, historian)</li></ul></li></ul>
Refining Domain Collaboration<ul><li>
Partner with process engineers, operations, maintenance, and planning teams to translate refinery problems into analytical solutions</li><li>
Incorporate first-principles knowledge (mass &amp; energy balances, constraints, process limits) into data models</li><li>
Interpret model results in the context of refinery economics, safety, and operability</li></ul>
Communication &amp; Impact<ul><li>
Clearly communicate insights to technical and non-technical stakeholders</li><li>
Quantify business impact (margin improvement, energy reduction, reliability gains)</li></ul> 

Requirements 
<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Chemical Engineering, Applied Mathematics, Statistics, or related field</li><li>
3&ndash;8+ years of experience applying data science in downstream refining or closely related process industries</li><li>
Strong proficiency in Python or R for data analysis and modeling</li><li>
Experience with time-series data and industrial process data</li><li>
Solid understanding of refining processes and unit operations</li><li>
Experience working with historians (PI), SQL databases, and unstructured data</li></ul>
Preferred Qualifications<ul><li>
Advanced degree (MS or PhD)</li><li>
Familiarity with:</li></ul>
Optimization techniques (LP/NLP)
Digital twin or hybrid physics + ML models
Cloud platforms (AWS, Azure, GCP)nced Data Scientists. 
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.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.</div>

Lead Data Scientist(Oil and Gas Industry)

Explore 308+ Ai computational data scientist in Houston United States this March. Find roles across top companies and apply now to boost your career.