predictive modeler

MANTECH

<div>MANTECH seeks a motivated, career- and customer-oriented Senior Data Scientist to join our innovative team in Ashburn, VA. This is a hybrid position with 2 days onsite and 3 days remote. 
Each day U.S. Customs and Border Protection (CBP) oversees the massive flow of people, capital, and products that enter and depart the United States via air, land, sea, and cyberspace. The volume and complexity of both physical and virtual border crossings require the application of &ldquo;big data&rdquo; solutions to promote efficient trade and travel. 
Responsibilities include but are not limited to:<ul><li>
Perform hands-on analysis and modeling involving the creation of intervention hypotheses and experiments, assessment of data needs and available sources, determination of optimal analytical approaches, performance of exploratory data analysis, and feature generation (e.g., identification, derivation, aggregation).</li><li>
Collaborate with mission stakeholders to define, frame, and scope mission challenges where big data interventions may offer important mitigations and develop robust project plans with key milestones, detailed deliverables, robust work tracking protocols, and risk mitigation strategies.</li><li>
Demonstrate proficiency in extracting, cleaning, and transforming CBP transactional and mission data associated within an identified problem space to build predictive models as well as develop appropriate supporting documentation.</li><li>
Leverage knowledge of a variety of statistical and machine learning techniques and methods to define and develop programming algorithms; train, evaluate, and deploy predictive analytics models that directly inform mission decisions.</li><li>
Participate in projects including those intended to identify patterns and/or anomalies in large datasets; perform automated text/data classification and categorization as well as entity recognition, resolution and extraction; and named entity matching.</li><li>
Brief project management, technical design, and outcomes to both technical and non-technical audiences including senior government stakeholders throughout the model development/project lifecycle through written as well as in-person reporting.</li></ul> 
Minimum Qualifications:<ul><li>
HS Diploma/GED and 15-20 years or AS/AA and 13-18 years or BS/BA and 7-12 years or MS/MA/MBA and 5-9 years or PhD/Doctorate and 3-7 years.</li><li>
Experience in developing machine learning models and applying advanced analytics solutions to solve complex business problems.</li><li>
Experience with programming languages including R, Python, Scala, Java, and proficiency with SQL programming.</li><li>
Proficiency with statistical software packages including SAS, SPSS Modeler, R, WEKA, or equivalent.</li><li>
Experience with pattern recognition and extraction, automated classification, and categorization and experience with entity resolution (e.g., record linking, named entity matching, deduplication/disambiguation).</li><li>
Experience with unsupervised and supervised machine learning techniques and methods and performing data mining, analysis, and training set construction.</li><li>
Experience with supervised machine learning methods including Decision Trees, Support Vector Machines, Logistic Regression, Random/Rotation Forests, Categorization/Classification, Neural Nets, Bayesian Networks, etc.</li></ul> 
Preferred Qualifications:<ul><li>
Experience constructing and executing queries to extract data in support of EDA and model development.</li><li>
Experience with visualization tools and techniques (e.g., Periscope, Business Objects, D3, ggplot, Tableau, SAS Visual Analytics, PowerBI).</li><li>
Experience with big data technologies (e.g., Hadoop, HIVE, HDFS, HBase, MapReduce, Spark, Kafka, Sqoop).</li><li>
Master&rsquo;s degree in mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience.</li></ul> 
Clearance Requirements:<ul><li>
Must be a U.S. Citizen and be able to obtain and maintain a CBP suitability prior to starting this position.</li></ul> 
Physical Requirements:<ul><li>
The person in this position needs to occasionally move about inside the office to access file cabinets, office machinery, or to communicate with co-workers, management, and customers, which may involve delivering presentations.</li></ul></div>

Senior Data Scientist

Cypher Games

<div>
 At Cypher Games, data isn&rsquo;t just numbers&mdash;it&rsquo;s the key to creating unforgettable player experiences. As a
 
 Data Scientist
 
 , you&rsquo;ll uncover patterns, build predictive models, and transform raw data into insights that shape the future of our games. Working hand-in-hand with Product, Marketing, and Engineering teams, your work will directly impact how millions of players enjoy and engage with our worlds. If you&rsquo;re passionate about games, analytics, and solving complex problems with creativity, we&rsquo;d love to have you on our team.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Analyze large and complex data sets to uncover insights that guide product, marketing, and design decisions
 </li>
 <li>
 Build predictive models, simulations, and forecasting tools to improve player engagement and retention
 </li>
 <li>
 Design and evaluate A/B tests to validate hypotheses and optimize gameplay and monetization strategies
 </li>
 <li>
 Collaborate with Product, Marketing, and Engineering teams to translate business needs into data-driven solutions
 </li>
 <li>
 Build and maintain dashboards, reports, and analytics pipelines to empower teams with actionable insights
 </li>
 <li>
 Monitor data quality and ensure the accuracy and reliability of reports and metrics
 </li>
 <li>
 Stay up-to-date with emerging tools, methods, and best practices in data science and analytics
 
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in a quantitative field (Statistics, Mathematics, Computer Science, Engineering, Economics, etc.)
 </li>
 <li>
 1&ndash;2+ years of professional experience in data science, analytics, or a related field (gaming experience is a plus)
 </li>
 <li>
 Strong skills in SQL and proficiency in Python
 </li>
 <li>
 Hands-on experience with dashboard and visualization tools (Looker, Tableau, or similar)
 </li>
 <li>
 Understanding of statistical methods, A/B testing, predictive modeling, and machine learning techniques
 </li>
 <li>
 Curiosity-driven, detail-oriented, and strong problem-solving mindset
 </li>
 <li>
 Excellent communication skills and ability to work in cross-functional teams
 </li>
 <li>
 Passion for mobile games and using data to shape player experiences
 
 </li>
 </ul>
</div>

Data Scientist

eInnoSys

Job Description: We are looking for an experienced Data Scientist to join our team and work on predictive modeling using manufacturing process data such as temperature, pressure, and other key sensor data. The ideal candidate should have at least 2 years of hands-on experience in the manufacturing sector, with a focus on building models to predict machine component failures. You don't need to be a Python expert, but you should be proficient in data science and have a strong understanding of machine learning algorithms applied to manufacturing data.Key Responsibilities:<ul><li>Analyze and model manufacturing process data (e.g., temperature, pressure, vibration, etc.) to identify trends and predict machine failures.</li><li>Develop machine learning models to predict equipment malfunctions, reduce downtime, and optimize maintenance schedules.</li><li>Work closely with engineering and operations teams to understand the dynamics of the machinery and design data-driven solutions.</li><li>Preprocess, clean, and transform raw manufacturing data into structured datasets for analysis.</li><li>Collaborate with cross-functional teams to integrate predictive models into real-time systems for continuous monitoring.</li><li>Present actionable insights from data analysis to stakeholders and recommend improvements for operational efficiency.</li><li>Monitor model performance and make improvements based on ongoing results and feedback from production environments.</li></ul>Required Qualifications:<ul><li>2+ years of experience as a Data Scientist in the manufacturing or industrial sector.</li><li>Strong knowledge of time-series analysis, anomaly detection, and predictive modeling techniques.</li><li>Experience with sensor data and process data from manufacturing machines (e.g., temperature, pressure, vibration).</li><li>Practical experience with machine learning algorithms and statistical analysis methods applied to failure prediction.</li><li>Proficient in data analysis tools such as R, SQL, and machine learning frameworks (e.g., Scikit-learn, TensorFlow).</li><li>Strong communication skills with the ability to convey technical results to non-technical stakeholders.</li><li>Ability to work in a fast-paced, collaborative environment and solve complex operational problems.</li></ul>Preferred Qualifications:<ul><li>Familiarity with cloud platforms (e.g., AWS, Azure) for data storage and analysis.</li><li>Experience with data visualization tools like Tableau or Power BI.</li><li>Understanding of predictive maintenance concepts and IoT integration.</li><li>Knowledge of MNC culture and experience working in a global environment.</li></ul>Benefits:<ul><li>5-day workweek</li><li>Flexible working hours</li><li>Supplemental Pay: Commission pay, Yearly bonus</li><li>Opportunity to work on patented products</li><li>International travel opportunities</li><li>A minimum of a 30% salary hike</li><li>MNC work culture</li><li>Month-end parties and Birthday celebrations</li></ul>Job Type: Full-timePay: &#8377;300,000.00 - &#8377;1,100,000.00 per yearBenefits:<ul><li>Health insurance</li><li>Paid time off</li></ul>Application Question(s):<ul><li>What's your Current CTC</li><li>What's your Expected CTC</li></ul>Experience:<ul><li>total work: 1 year (Preferred)</li></ul>Work Location: In person

Cotiviti

<div>Overview:
<div>
We are seeking an Advanced AI researcher directing the development of predictive models and decision systems for Claims Operations, focusing on data driven insights and workflow optimization.</div>
Responsibilities:
<ul><li>Lead the design of advanced predictive models for Claims Operations.</li><li>
Oversee feature engineering and model development.</li><li>
Design analytical frameworks for data driven decision making.</li><li>
Establish evaluation frameworks for model performance and accuracy.</li><li>
Lead knowledge transfer and mentorship for AI/ML techniques.</li><li>
Drive innovation in analytics approaches and methodologies.</li></ul>
Qualifications:
<ul><li>7+ years in ML/AI with focus on advanced analytics and predictive modeling.</li><li>
Experience building and deploying production AI/ML models.</li><li>
Expertise in data mining and pattern recognition techniques.</li><li>
Strong background in model evaluation and performance metrics.</li><li>
Experience with healthcare analytics and claims processing workflows.</li><li>
Knowledge of statistical analysis and hypothesis testing methodologies.</li></ul></div>

Lead Data Scientist

EjadTech - إيجاد التقنية

<div>
 
 To analyze large and complex datasets using statistical methods and machine learning algorithms, deriving valuable insights that support strategic decision-making and enhance organizational performance.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 Collect, clean, and prepare data from various internal and external sources.
 
 
 Design and build predictive models using Machine Learning and AI techniques.
 
 
 Apply advanced statistical analysis to discover hidden patterns and relationships.
 
 
 Develop interactive dashboards and reports using Business Intelligence tools (Power BI, Tableau).
 
 
 Collaborate with cross-functional teams (IT, Development, Business) to translate needs into analytical solutions.
 
 
 Monitor, validate, and continuously improve model performance.
 
 
 Present findings and provide actionable recommendations to senior management.
 
 
 Stay up to date with the latest trends in data science and emerging technologies.
 
 
 
 
 
 
 Qualifications:
 
 
 
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Statistics, Mathematics, Data Science, or a related field.
 
 
 Minimum of 3 years of professional experience in data analysis, data science, or predictive modeling.
 
 
 Proficiency in programming languages (Python, R, SQL).
 
 
 Knowledge of Big Data tools (Hadoop, Spark) is a plus.
 
 
 Strong skills in data visualization and reporting.
 
 
 Excellent analytical thinking and problem-solving abilities.
 
 
 Strong communication skills and ability to work in a team environment.
 
 
 
 
 
 
 Core Skills:
 
 
 
 Statistical Data Analysis
 
 
 Machine Learning &amp; Artificial Intelligence
 
 
 Business Intelligence (BI) Dashboards
 
 
 Database Management (SQL/NoSQL)
 
 
 Data Interpretation &amp; Storytelling for Non-Technical Stakeholders
 
</div>

Midas Games

<div>
 
 The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.&nbsp;
 
 
 &nbsp;
 
 
 Responsibilities
 
 <ul>
 <li>
 Analyze raw data: assessing quality, cleansing, structuring for downstream processing
 </li>
 <li>
 Design accurate and scalable prediction algorithms
 </li>
 <li>
 Collaborate with engineering team to bring analytical prototypes to production
 </li>
 <li>
 Generate actionable insights for business improvements
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree or equivalent experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
 </li>
 <li>
 At least 1 - 2 years' of experience in quantitative analytics or data modeling
 </li>
 <li>
 Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms
 </li>
 <li>
 Fluency in a programming language (Python, C,C++, Java, SQL)
 </li>
 <li>
 Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau)
 </li>
 </ul>
 
</div>

Cleveland Clinic Abu Dhabi

<div>
 
 JOB SUMMARY
 
 
 The Data Scientist will extract and analyze large datasets from a range of heterogenous business applications, most
 
 
 importantly the electronic medical record EMR. Using statistical, artificial intelligence and machine learning tools and
 
 
 algorithms, the data scientist will discover and offer insights into the data. They will design, develop, build and validate
 
 
 predictive, machine learning and AI models based on requirements and communicate the results in an understandable
 
 
 manner, and once approved by the business, the algorithms and models will be deployed into the production
 
 
 environment.
 
 
 
 
 
 PRIMARY JOB DUTIES AND RESPONSIBILITIES:
 
 
 &middot; Collaborate with the business stakeholders to document the business requirements, anticipated benefits, and
 
 
 success criteria for analytics initiatives
 
 
 &middot; Collaborate with subject matter experts to define the use case and to prepare an exhaustive set of potential features for analysis &middot; Perform feature engineering for optimization and dimensionalityreduction &middot; Perform advanced descriptive and diagnostic analytics (Exploratory Data Analysis) &middot; Perform Data Profiling &middot; Extract, process, clean, and validate quality datasets &middot; Assist data engineers in implementing data pipelines &middot; Conduct Experiment Design &middot; Identify multiple predictive, machine learning and AI algorithms that potentially fit the business case &middot; Write general, reusable code for repeatable analysis &middot; Evaluate and tune the models using various performance and error measures, hyper parameter tuning and cross validation techniques &middot; Select the final model based on performance &middot; Document and present the model findings to the business by explaining the model assumptions and validation methodologies &middot; Deploy the model by integrating it with the EMR or other business applications / systems &middot; Monitor the model for data and concept drift and retrain or tune the model as required &middot; Build visual interfaces with &ldquo;what-if&rdquo; functionality for business user interaction.
 
 
 
 
 
 ROLE LEVEL ACCOUNTABILITIES
 
 
 &middot; Adheres to CCAD&rsquo;s standards as they appear in the Code of Conduct and Conflict of Interest policies
 
 
 
 
 
 In view of the evolving needs and opportunities within CCAD, this position may be required to perform other duties
 
 
 as assigned and reporting relationships may vary.
 
 
 
 
 
 ORGANIZATION-WIDE COMPETENCY ASSESSMENT REQUIREMENTS:
 
 
 All employees will embrace the CCAD mission, vision and values and be responsible for adhering to the core values of the institution, including: Patient&rsquo;s First, Collaboration, Mutual Respect, Quality, Patient Safety, Integrity, Cultural Sensitivity and Compassion. All employees are also expected to meet the standards of performance outlined in the Organization-Wide Competencies listed below as applied to the position. Customer Service Orientation includes attitude, behavior, interpersonal skill and problem solving that enable an employee to respond to internal and external customer needs and expectations in a positive manner. Adaptability including teamwork, flexibility needed to fulfill job responsibilities, adapting to changes in work environment and accepting supervisory feedback. Efficiency and Effectiveness includes quantity and quality of desired work, as well as organization skills necessary to perform successfully. Essential Job Requirements includes adherence to all relevant policies, procedures and guidelines affecting the work environment, as well as maintenance of required competencies and communication skills. Managerial Responsibilities includes overall accountability for assigned work group relative to operational goals, personnel requirements and budgetary constraints.
 
 
 
 
 
 Education Bachelors in a relevant field such as Statistics, Computer Science, Data Science, Mathematics, Physics Masters in a relevant field such as Statistics, Computer Science, Data Science, Mathematics, Physics
 
 
 Experience 5+ years 3+ years
 
 
 Certification and
 
 
 Licensure
 
 
 Professional
 
 
 Membership
 
 
 Job Specific Skills and
 
 
 Abilities &middot; Excellent oral and written communication skills. &middot; Experience with Principal Component Analysis and Linear Discriminant analysis &middot; Experience with Visual Analytics tools &middot; Experience with Correlations, Clustering, Imputation, De-skewing, Normalization and Outlier Analysis &middot; Experience with statistical analysis, Inferential statistics, hypothesis testing, Bayesian statistics, probability theory, Exploratory data analysis, Correlation - Regression analysis, design of experiments, sample size calculation etc. &middot; Experience with extracting data from database management systems &middot; Experience with transformation and cleaning of both structured and unstructured data &middot; Experience with Agile Software Development methodologies &middot; Experience with Software Engineering &middot; Experience in predictive modelling, Time series analysis, machine learning, neural networks, deep learning and reinforcement learning. Deep knowledge of traditional ML concepts such as GLMs, GMMs, SVMs, &middot; Healthcare experience is preferred
 
 
 random forest, regression , decision trees, and boosting. &middot; Experience with AI models, Tensorflow, Open AI, LLMs &middot; Experience with MLOPS, LLMOPS, deploying models into production &middot; Experience with User Interface (UI) development Experience with the following software: &middot; Cloud Platforms: Fabric, Azure, AWS, GCP &middot; Database Management Systems MS SQL Server, Azure Data Lake, Azure Synapse &middot; Data Wrangling: MS SSIS, Azure Data Factory &middot; Statistical Analysis Software: SAS, SPSS, Minitab &middot; Version Control: GitHub &middot; Platform: Databricks, Azure ML &middot; Scripting Language: Python / R and libraries (Pandas, NumPy, Seaborn, Matplotlib) &middot; Query Language: SQL &middot; Other Languages: Spark SQL &middot; AI &amp; ML Frameworks : TensorFLow, Keras , PyTorch , GANs, CNN, Caffe, Scikit-learn, Spark ML &middot; Deployment Software: Docker &middot; Visual Analytics: Power BI, Tableau, Minitab, Excel &middot; UI Tools: Shiny, Power Apps
 
 
 
</div>

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