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Society of Exploration Geophysicists

Senior Consultant - Senior Data Scientist

Society of Exploration Geophysicists, Dallas, Texas, United States, 75215


About NeudesicPassion for technology drives us, but it’s innovation that defines us. From design to development and support to management, Neudesic offers decades of experience, proven frameworks and a disciplined approach to quickly deliver reliable, quality solutions that help our customers go to market faster.What sets us apart from the rest is an amazing collection of people who live and lead with our core values. We believe that everyone should be

Passionate

about what they do,

Disciplined

to the core,

Innovative

by nature, committed to a

Team

and conduct themselves with

Integrity.

If these attributes mean something to you - we'd like to hear from you.Role SummaryNeudesic is currently seeking a Senior Data Scientist for our Data & AI Practice. This role requires the perfect mix of being a brilliant technologist and also a deep appreciation for how technology drives business value. You will have broad and deep technology knowledge and the ability to architect solutions by mapping client business problems to end-to-end technology solutions. Demonstrated ability to engage senior level technology decision makers in data management, real-time analytics, predictive analytics and data visualization is a must.To be successful, you must exhibit strong leadership qualities necessary for building trust with clients and our technologists, with the ability to deliver ML/DL projects to successful completion. You will partner with solution architects to drive client success by providing practical guidance based on your years of experience in data management and visualization solutions. You will partner with a diverse sales unit to professionally represent Neudesic experience and ability to drive business results. In addition, you will assist in creating sales assets that clearly communicate our value proposition to technical decision makers.Requirements:At least 3+ years of hands-on mathematical modeling experience in business environmentBachelor’s degree in quantitative field like Computer Science, Engineering, Business Analytics, Statistics, Mathematics or related field required. Advanced degree is a strong plusExperience with Databricks is requiredExperience in R/Python and SQLKnowledge of statistical, data mining, machine learning (ML and MLOps), large language model (LLM) and AI techniques (regression, decision trees, clustering, neural networks, and deep learning frameworks, etc.)Strong SQL skills and proven experience in working with large datasets and relational databasesPreferred QualificationsExperience in Hadoop, Spark, and cloud platform experienceExperience in working with big data tools/environment, e.g. Hadoop Ecosystem (write complex HQL query, automate production pipeline, etc.), Spark, is a strong plusExperience with data visual analysis and BI tools like Tableau and Power BIProven experience in working with cloud computing platforms particularly Azure is a strong plusDistinctive communications skills and ability to communicate analytical and technical content in an easy-to-understand wayAbility to tell stories and make recommendations with data exploratory/visual analysisIntellectual curiosity, along with excellent problem-solving and quantitative skills, ability to disaggregate issues, identify root causes and recommend solutionsResult-driven achievers and proven leaders with the ability to inspire others, build strong relationships, and create a true followershipStrong people skills, team-orientation, and a professional attitudeMore about our Predictive Enterprise Service Line:The digital business uses data as a competitive differentiator. The explosion of big data, machine learning and cloud computing power creates an opportunity to make a quantum leap forward in business understanding and customer engagement. The availability of massive amounts of information, massive computing power and advancements in artificial intelligence allow the digital business to more accurately predict, plan for and capture opportunity unlike ever before. The predictive enterprise service line the evolution from using data strictly as a reporting mechanism of what’s happened to leveraging the latest in advanced analytics to predict and prescribe future business action. Our services include:·

Data Management Solutions:

We build architectures, policies, practices and procedures that manage the full data lifecycle of an enterprise. We bring internal and exogenous datasets together to formulate new perspectives and drive to data-thinking.·

Self-Service Data Solutions:

We create classic self-service and modern data-blending solutions that enable end-users to enrich pre-authored analytic reports by blending them with additional data sources.·

Real-Time Analytic Solutions:

We build real-time analytics solutions on data-in-motion that eliminate the dependency on stale and static data sets resulting in the ability to immediately query and analyze diverse data sets.·

Machine Learning Solutions:

We build machine-learning solutions that support the most complex decision support systems.Neudesic also offers professional development and training for our Consultants. This includes opportunities to gain new technical certifications, develop professionally and grow within the company.Accommodations currently remain in effect for Neudesic employees to work remotely, provided that remote work is consistent with the work patterns and requirements of their team’s management and client obligations. Subject to business needs, employees may be required to perform work or attend meetings on-site at a client or Neudesic location.Neudesic is an Equal Opportunity EmployerAll employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.

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