6,107 Data Mining jobs in the United States

SystImmune is a biotech company dedicated to developing innovative therapies for various diseases. We are seeking an experienced Machine Learning Scientist with expertise in data mining to join our team. The successful candidate will play a key role in analyzing pre-clinical and/or clinical data to uncover new protein targets and identify potential drug optimization opportunities for immunotherapy in cancers and other diseases. We are looking for a highly skilled Machine Learning Scientist with experience in data mining to analyze large datasets from public domain or company internal data. The ideal candidate will have a strong background in machine learning, data analysis, and programming skills. The primary objective of this role is to use AI, computational biology, and bioinformatics methods to classify and process R&D data, identifying potential opportunities for drug optimization and protein targets for immunotherapy. Responsibilities: Data Mining: Apply data mining techniques to large datasets from clinical trials, using desensitized data to identify patterns, trends, and correlations. Machine Learning Model Development: Design, develop, and train machine learning models to classify and process R&D data, identifying potential opportunities for drug optimization. Protein Target Identification: Use AI, computational biology, and bioinformatics methods to identify protein targets of immunotherapy in cancers and other diseases. Data Analysis: Analyze and interpret results from data mining and machine learning models, providing insights and recommendations to cross-functional teams. Collaboration: Work closely with researchers, clinicians, and other stakeholders to ensure that data analysis and machine learning models are aligned with business objectives and research goals. Communication: Present findings and results to both technical and non-technical audiences, including written reports, presentations, and visualizations. Requirements: Master's or Ph.D. in Computer Science, Machine Learning, Biostatistics, Bioinformatics, or a related field. 3+ years of experience in machine learning, data mining, or a related field, with a focus on clinical trial data analysis. Technical Skills: Proficiency in programming languages such as Python, R, or SQL. Experience with machine learning frameworks such as TensorFlow, or PyTorch. Familiarity with data visualization tools such as Tableau, Power BI, or D3.js. Domain Knowledge: Strong understanding of clinical trial design, biostatistics, and immunotherapy principles. Communication Skills: Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams. Nice to Have: Familiarity with containerization using Docker. Knowledge of data security and compliance regulations such as HIPAA. Experience with agile development methodologies and version control systems such as Git. Company Culture: At SystImmune, we value innovation, collaboration, and creativity. We believe in fostering a work environment that is supportive, inclusive, and stimulating. Our team members are passionate about their work and are committed to making a positive impact on the lives of patients. SystImmune is committed to creating a diverse and inclusive work environment. Our goal is to build a team that reflects the diversity of our community and provides equal opportunities for everyone to succeed. If you share our values and are looking for a challenging and rewarding career opportunity, we encourage you to apply. About Our Team: Our team consists of experienced professionals from various backgrounds, including computer science, biostatistics, bioinformatics, and immunology. We work closely together to develop innovative solutions that can improve patient outcomes. If you are a motivated and talented individual who is passionate about machine learning and data analysis, we would love to hear from you. What to Expect: As a Machine Learning Scientist at SystImmune, you can expect to work on challenging projects that require the application of machine learning techniques to real-world problems. You will have the opportunity to collaborate with cross-functional teams, including researchers, clinicians, and data scientists. You will also have access to cutting-edge technologies and tools, as well as professional development opportunities to help you grow in your career. Compensation and Benefits: The expected base salary range for this position is $100,000 - $180,000 annually. Actual compensation will be based on a variety of factors, including but not limited to a candidate’s qualifications, experience, and skills. While most offers typically fall within the low to mid-point of the range, we may extend an offer toward the higher end for exceptional candidates whose background and expertise align strongly with the requirements of the role. SystImmune is a leading and well-funded biotech company with a bright future. We offer an opportunity for you to learn and grow while making significant contributions to the company’s success. SystImmune offers a comprehensive benefits package including: 100% paid employee premiums for medical/dental/vision, also STD, LTD, a 401(k) plan with a 50% company match of up to 3% and a vesting schedule of only 5 years, 15 PTO days per year, sick leave, plus 11 paid holidays and MORE. We offer an opportunity for you to learn and grow while making significant contributions to the company’s success. SystImmune is an Equal Opportunity Employer. We welcome diverse talent and encourage all qualified applicants to apply. #J-18808-Ljbffr

Sagility combines industry-leading technology and transformation-driven BPM services with decades of healthcare domain expertise to help clients draw closer to their members. The company optimizes the entire member/patient experience through service offerings for clinical, case management, member engagement, provider solutions, payment integrity, claims cost containment, and analytics. Sagility has more than 25,000 employees across 5 countries.

Job title:

Data Mining Consultant (Client Lead)

Job Description:

We are currently hiring a talented Consultant II, Lead Consultant Data Supervisor. This is a client facing role responsible for leading a team of experienced professionals in identifying new audit opportunities, researching pricing methodologies, and engaging with various work teams to generate systems automation and enhancement capabilities in our state-of-the-art audit workstation. In this role you will develop, train, and manage a team of dedicated professionals to ensure client targets and KRA's are met while also acting as an individual contributor in these areas.

Key Requirements:

• Review and analyze payment-related data using data mining techniques to ensure accuracy, compliance, and fraud prevention in financial transactions.
• Lead team members to meet targets.
• Ideate and perform audits on payment data, identifying discrepancies, errors, and fraudulent activities, and providing recommendations for process improvement.
• Manage the supervision, training, and development of their team as well as the data collection, data analytics and data reporting for data mining programs including but not limited to COB, Duplicate, Contractual, billing errors, and overlapping services.
• Participate in client meetings and lead pertinent discussions.
• Communicate client claims payment practices and ensure information shared with their team.

Education, Experience, and Skills:

• 5+ year?s knowledge of direct claim processing/reimbursement, medical facility contracts, fee schedules, inpatient/outpatient/physician claims required.
• 3 or more years of management experience in claims processing is a strong plus.
• Experience Ideating & developing new auditing rules and paradigms.
• Experience in business case analysis and help designing BRD, pricing, COB, platform analytics.
• Experience of Validation of Rules through testing methodologies, auditing, payment processing, or financial fraud prevention is a must.
• Load and synthesize healthcare data from multiple sources.
• Experience working within a health plan, managed care organization, provider operated healthcare environment or third-party administrator.
• Development of end-to-end payment Integrity reports like Data Intake, Audit Selections, Findings, Appeals, Medical record Management, Audit Operations, Recovery Operations, Provider Correspondence and Forecasting & Invoicing.
• Maintaining a working knowledge of CMS transmittals, RAC, and OIG reports is a must.
• Prior claims auditing or consulting experience desirable in either a provider or payer environment.
• Provide recommendations for improving payment integrity processes, fraud prevention measures, and operational efficiency based on audit findings.
• Work with audit teams and establish a process to ensure the concepts being deployed are working as expected with higher findings thus ensuring higher hit rates and findings rates on the concepts deployed.
• Excellent communication skills both oral and written.
• Strong interpersonal skills that will support collaborative teamwork.
• Microsoft Office Proficient: Word and Excel; Access ? highly preferred
• Ability to interpret and assess complex payment datasets.
• Excellent communication and interpersonal skills.

Sagility Offers Competitive Benefits Including:

• Medical
• Dental
• Vision
• Life Insurance
• Short-Term and Long-Term Disability
• Flexible Spending Account
• Life Assistance Program
• 401K with employer contribution
• PTO and Sick Time
• Tuition Reimbursement

Join our team, we look forward to talking with you!

An Equal Opportunity Employer/Vet/Disability

Location:

USAUnited States of America

• Develop, implement, and maintain predictive models and machine learning algorithms to optimize various aspects of mining operations, including ore body modeling, equipment predictive maintenance, production forecasting, and process optimization.
• Collect, clean, and preprocess large, complex datasets from diverse sources within mining operations (e.g., sensors, geological surveys, production systems).
• Perform rigorous statistical analysis to identify trends, patterns, and correlations that impact operational efficiency and safety.
• Design and build interactive dashboards and data visualizations to present complex analytical findings in an accessible and understandable format to technical and non-technical stakeholders.
• Collaborate with geologists, engineers, operations managers, and IT teams to understand business challenges and translate them into data-driven solutions.
• Evaluate the effectiveness of implemented models and algorithms, iterating and refining them for continuous improvement.
• Research and evaluate new data science tools, technologies, and methodologies relevant to the mining industry.
• Contribute to the development of data governance frameworks and best practices for data quality and integrity.
• Document models, methodologies, and findings clearly and concisely.
• Identify opportunities for leveraging new data sources and technologies to enhance analytical capabilities.
• Participate in cross-functional projects, providing data science expertise and strategic insights.
• Ensure compliance with data privacy and security regulations.
• Mentor junior data scientists and contribute to a culture of continuous learning.

• Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 5+ years of experience in data science, with a strong portfolio demonstrating expertise in machine learning, statistical modeling, and data analysis.
• Proven experience working with large, complex datasets, ideally in industrial, heavy machinery, or resource extraction sectors.
• Expert proficiency in programming languages such as Python (with libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and/or R.
• Strong experience with SQL and NoSQL databases.
• Proficiency in data visualization tools (e.g., Tableau, Power BI, Plotly, D3.js).
• Understanding of geological data, mining processes, and operational technology (OT) systems is highly desirable.
• Excellent problem-solving skills and the ability to translate business problems into analytical solutions.
• Strong communication and presentation skills, with the ability to explain complex analytical concepts to diverse audiences.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) for data storage and processing is a plus.
• Knowledge of big data technologies (e.g., Spark, Hadoop) is an advantage.
• Ability to work independently and collaboratively in a fast-paced, innovative environment.

• Lead the collection, processing, and analysis of large, complex datasets from various mining operations (e.g., production, logistics, equipment performance, geological surveys).
• Develop and implement predictive models, statistical analyses, and data visualizations to identify trends, anomalies, and opportunities for optimization.
• Translate complex data findings into clear, concise, and actionable recommendations for stakeholders, including operational managers and executives.
• Design and maintain dashboards and reports that provide real-time insights into key performance indicators (KPIs) for mining processes.
• Collaborate with engineering and product teams to integrate data solutions into operational systems and software platforms.
• Mentor and guide junior data analysts, fostering their professional growth and technical skills.
• Stay current with emerging data science techniques, tools, and best practices, particularly those relevant to industrial applications.

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field.
• 6+ years of experience in data analysis, with a significant portion focused on large-scale operational data.
• Expert proficiency in SQL and Python or R for data manipulation, analysis, and statistical modeling.
• Strong experience with data visualization tools (e.g., Tableau, Power BI, Looker).
• Demonstrated ability to lead analytical projects and deliver impactful data-driven insights.
• Excellent problem-solving skills and attention to detail.

• Experience with big data technologies (e.g., Hadoop, Spark).
• Knowledge of machine learning algorithms and their application in predictive maintenance or operational optimization.
• Familiarity with geological data or industrial sensor data.

• Lead the design, development, and deployment of predictive models and machine learning algorithms to address key challenges in mining operations (e.g., equipment predictive maintenance, ore grade optimization, production forecasting, safety analytics).
• Collaborate with domain experts, engineers, and operational teams to identify data-driven opportunities and translate business problems into analytical solutions.
• Collect, clean, and preprocess large, complex datasets from various sources, including sensor data, operational logs, and geological surveys.
• Perform exploratory data analysis to uncover insights, patterns, and anomalies.
• Develop and implement data pipelines and robust ETL processes.
• Evaluate model performance, conduct A/B testing, and iterate on models to ensure continuous improvement and business impact.
• Communicate complex analytical findings and recommendations clearly and concisely to both technical and non-technical stakeholders.
• Stay abreast of the latest advancements in data science, machine learning, and mining technology, applying relevant techniques.
• Mentor junior data scientists and contribute to best practices in data science methodologies and MLOps.
• Create compelling data visualizations and interactive dashboards to present insights.
• Contribute to the strategic direction of data science initiatives within the company.
• Ensure data privacy and security compliance in all data handling and analysis.
• Provide technical leadership in selecting appropriate data science tools and platforms.
• Publish internal reports and potentially external white papers on findings.
• Participate in client-facing discussions to understand requirements and present solutions.

• Master’s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 5-7+ years of experience as a Data Scientist, with a strong portfolio of successfully deployed projects.
• Expert proficiency in Python or R and relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas, NumPy).
• Strong experience with SQL and working with large-scale databases.
• Experience with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop).
• Demonstrated expertise in machine learning techniques (regression, classification, clustering, time series analysis, deep learning).
• Experience with geospatial data analysis or industrial IoT data is highly desirable.
• Excellent problem-solving skills and the ability to work with ambiguous data.
• Strong communication and presentation skills, with the ability to convey complex analytical concepts to diverse audiences.
• Experience in the mining, energy, or heavy industry sectors is a significant advantage.
• Proficiency in data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
• Familiarity with MLOps practices and tools.
• Ability to work independently and collaboratively in a fast-paced environment.

• Collect, process, and analyze large volumes of geospatial data from various sources (e.g., satellite imagery, LiDAR, drone surveys, ground-based sensors) specific to mining operations.
• Develop and implement advanced algorithms and models for geospatial analysis, mapping, and visualization of geological features, resource estimation, and mine planning.
• Utilize GIS software (e.g., ArcGIS, QGIS) and programming languages (e.g., Python with libraries like GeoPandas, Rasterio) to extract actionable insights from geospatial data.
• Collaborate with mining engineers, geologists, and software developers to integrate geospatial data into mining planning, operations, and monitoring systems.
• Create high-quality maps, reports, and interactive dashboards to present complex geospatial information to internal teams and clients.
• Ensure data accuracy, integrity, and consistency across all geospatial datasets.
• Identify opportunities to leverage new geospatial technologies and data sources to improve mining efficiency, safety, and environmental compliance.
• Assist in the development of predictive models for resource management and operational optimization.
• Troubleshoot and resolve data quality issues related to geospatial information.
• Contribute to the design and improvement of geospatial data infrastructure and pipelines.
• Stay abreast of industry trends in geospatial technology, data science, and the mining sector.
• Provide technical support and training to users on geospatial tools and data.
• Document methodologies, processes, and data dictionaries for all geospatial analyses.

• Bachelor's or Master's degree in Geospatial Science, Geoinformatics, Geography, Remote Sensing, Data Science, or a related field.
• Minimum of 3-5 years of professional experience in geospatial data analysis, with a focus on large-scale datasets.
• Strong proficiency in GIS software (ArcGIS, QGIS) and spatial databases (e.g., PostGIS).
• Expertise in Python programming with experience in geospatial libraries (e.g., GeoPandas, Shapely, Rasterio) and data science libraries (e.g., Pandas, NumPy).
• Experience with remote sensing data processing and analysis.
• Understanding of mining operations, geology, and resource management is highly desirable, or a strong willingness to learn.
• Familiarity with cloud-based geospatial platforms (e.g., Google Earth Engine, AWS GIS services) is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong visualization skills and experience creating informative maps and dashboards.
• Exceptional written and verbal communication skills, able to convey complex technical information clearly.
• Ability to work independently and as part of a collaborative, cross-functional team.
• Experience with machine learning applied to geospatial data is a significant advantage.

• Develop and refine algorithms and software modules for geological data processing, modeling, and visualization within our client's mining software suite.
• Analyze large datasets from geological surveys, drilling campaigns, and resource estimation, identifying patterns and anomalies.
• Collaborate with geologists, mining engineers, and software developers to translate industry needs into technical specifications for new software features.
• Design and implement data quality control procedures for geological data to ensure accuracy and reliability.
• Create interactive data dashboards and reports that provide actionable insights for mining exploration and production.
• Provide technical support and training to clients on the use of geological data analysis tools.
• Perform geological modeling and resource estimation using specialized software, validating results against real-world data.
• Participate in the full software development life cycle, from conceptualization and design to testing and deployment.
• Stay current with advancements in geological data acquisition technologies, geological modeling techniques, and data science methodologies.
• Assist in the integration of various geological and mining datasets from disparate sources.
• Conduct performance testing and optimization of data processing workflows.
• Document software functionalities, user guides, and technical specifications related to geological data analysis.
• Troubleshoot data-related issues and provide solutions to complex geological challenges within the software context.
• Contribute to the continuous improvement of the product based on user feedback and industry trends.

• Bachelor's or Master's degree in Geology, Geological Engineering, Geoinformatics, or a related field with a strong emphasis on data analysis.
• 3-7 years of experience in geological data analysis, preferably within the mining or exploration industry.
• Proficiency with geological modeling software (e.g., Leapfrog Geo, Micromine, Surpac, GEMS) and GIS software (e.g., ArcGIS, QGIS).
• Strong skills in data manipulation and analysis using programming languages such as Python (Pandas, NumPy) or R.
• Experience with database management systems (SQL, NoSQL) for handling large geological datasets.
• Understanding of geological principles, mineral resource estimation, and exploration methodologies.
• Familiarity with statistical analysis techniques for spatial data.
• Excellent analytical, problem-solving, and critical thinking skills, with attention to detail.
• Strong verbal and written communication skills, capable of explaining complex technical concepts to both technical and non-technical audiences.
• Ability to work independently and collaboratively in a cross-functional software development team.
• Experience with cloud platforms (AWS, Azure) and data visualization tools (Tableau, Power BI) is a plus.
• Knowledge of machine learning applications in geology is highly desirable.

• Collect, clean, and organize large datasets from various sources related to global mining operations, commodity prices, production volumes, and environmental metrics.
• Develop and implement data models, dashboards, and reports to visualize key performance indicators (KPIs) and trends relevant to the mining sector.
• Perform statistical analysis and complex queries to identify patterns, correlations, and anomalies in operational and market data.
• Provide data-driven insights and recommendations to support investment decisions, operational improvements, and strategic planning.
• Collaborate with geologists, engineers, financial analysts, and investment teams to understand their data needs and deliver tailored analytical solutions.
• Automate data collection and reporting processes using scripting languages (e.g., Python, R) and business intelligence tools.
• Ensure data integrity, accuracy, and security across all analytical platforms.
• Stay abreast of technological advancements in data analytics and their application to the mining industry.
• Assist in the development and validation of predictive models for commodity prices, production forecasts, and market movements.
• Prepare clear and concise presentations to communicate complex analytical findings to non-technical stakeholders.
• Support due diligence processes for potential acquisitions or partnerships by providing robust data analysis.
• Contribute to the continuous improvement of data analytics capabilities within the firm.

• Bachelor's or Master's degree in Data Science, Statistics, Engineering (Mining, Industrial, or related), Finance, or Economics.
• 3-5 years of experience in data analysis, business intelligence, or a similar quantitative role.
• Experience with large datasets and strong proficiency in SQL.
• Proficiency in at least one statistical programming language (Python or R) and data visualization tools (e.g., Tableau, Power BI).
• Understanding of the mining industry, commodity markets, or natural resources sector is highly desirable.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to translate complex data into actionable insights.
• Detail-oriented with a strong commitment to accuracy and data integrity.
• Ability to work independently and collaboratively in a fast-paced environment.
• Familiarity with cloud platforms (AWS, Azure, GCP) for data storage and processing is a plus.

job summary:
Responsibilities

• We are seeking an experienced Machine Learning Engineer to join our AI/ML Engineering team.
• You will be responsible for developing and optimizing complex data pipelines, integrating model pipelines, and building scalable AI/ML solutions, including large language models (LLMs).

• The ideal candidate will possess a robust background in traditional machine learning, deep learning, and significant experience with large datasets and cloud-based AI services.
• Develop and optimize complex data pipelines, applying machine learning engineering principles to enhance efficiency and scalability.
• Integrate and optimize data and model pipelines within production environments, diagnosing data inconsistencies and documenting assumptions.
• Collaborate with data science teams to review model-ready datasets and feature documentation, ensuring completeness and accuracy.
• Perform data discovery and analysis of raw data sources, applying business context to meet model development needs.
• Comfort with exploratory data exploration and tracking data lineage during inception or root cause analysis.
• Write and maintain model monitoring scripts, diagnosing issues and coordinating resolutions based on alerts.

• Around 5-8 years of relevant work experience.
• At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker).
• Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.
• Strong understanding of cloud technologies, including AWS and Azure.
• Experience with API design and development is a plus.

• Solid understanding of software engineering principles, including design patterns, testing, security, and version control.
• Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.