Prescience Decision Solutions

Prescience Decision Solutions is looking for Data Scientist to join our dynamic team and embark on a rewarding career journey. Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Prescience Decision Solutions is looking for Data Scientist to join our dynamic team and embark on a rewarding career journey. Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Prescience Decision Solutions is looking for Data Applications Engineer /Data Application Specialist to join our dynamic team and embark on a rewarding career journey. Collaborating on software development projects with the engineering, sales, and customer services departments. Liaising with clients and incorporating user-defined needs and feedback into application designs. Writing code and scripts for applications, as well as installing, maintaining, and testing applications. Providing clients with technical support. Optimizing applications by integrating new technologies and performing upgrades. Contributing to sales presentations, as well as demonstrating prototypes and completed applications. Performing diagnostic tests and debugging procedures, as well as improving code and re-designing tasks. Generating ideas for software innovation based on market trends. Documenting development processes, procedures, and application version histories. Superb collaboration and communication skills. Excellent analytical and problem-solving skills.

Role Overview: We are looking BI + data-engineer kind of skills. The main work is to design & build complex Tableau dashboards, set up robust automated data pipelines and backend tables and do this in an optimized manner. There is also LLM integration into the dashboard, which will require some initiative and exploration. Automations + LLM integration would require some Python experience Job Description: Requirements 3+5 Years of experience in a product analytics, data analyst, or analytics product role Hands on experience in advanced SQL, python Advanced Tableau experience (Min 2yrs hands on experience in Tableau mandatory) Experience in LLM integration into the dashboard • Proven ability to support and improve analytical products that drive business decisions Roles and Responsibilities: Product Thinking & Ownership Product development exposure : Experience working on analytics or data products throughout the product lifecycle - from requirements to delivery. Prioritization skills : Can independently manage a backlog, help triage requests and contribute to roadmap planning. Analytical & Technical Proficiency Strong SQL skills : Can write and optimize queries to explore data and validate product behavior or outcomes. Data visualization : Comfortable building dashboards or reports in tools like Tableau Cross-functional skills : Experience working with product managers, analysts, and engineers to drive product outcomes. Comfort with data pipelines : Understands how data flows through systems; collaborates effectively with data engineers and analytics teams. Model consumption : Understands the basics of AI/ML model outputs and how they feed into products

Prescience Decision Solutions is looking for Senior Data Analyst to join our dynamic team and embark on a rewarding career journey. The Senior Data Analyst is responsible for analyzing large datasets, interpreting data, and providing actionable insights to support business decision - making. They will work closely with cross - functional teams to identify data needs, design data collection methods, perform data analysis, and communicate findings to stakeholders. The Senior Data Analyst plays a crucial role in driving data - driven strategies and improving overall business performance. Key Responsibilities:Collect, clean, and transform large datasets from various sources to ensure data accuracy and integrity. Analyze complex datasets using statistical techniques and data mining methods to identify trends, patterns, and insights. Interpret and communicate findings to both technical and non - technical stakeholders through reports, visualizations, and presentations. Collaborate with cross - functional teams to understand business requirements and develop data analysis plans to address specific objectives. Develop and maintain data models, dashboards, and reports to provide ongoing performance metrics and KPIs. Identify data quality issues, perform data validation, and implement data cleaning and data normalization processes. Utilize data visualization tools (e. g. , Tableau, Power BI) to create interactive dashboards and visual representations of data. Stay updated with industry trends, emerging technologies, and best practices in data analysis and data management. Identify opportunities to optimize data collection, analysis, and reporting processes, and implement efficient and automated solutions. Mentor and provide guidance to junior data analysts, fostering their professional growth and development. Qualifications and Skills:Bachelor's degree in statistics, mathematics, computer science, or a related field. A master's degree is a plus. X years of experience as a Data Analyst, preferably in a senior or lead role. Proficiency in statistical analysis tools such as R, Python, or SAS. Strong knowledge of data analysis techniques, including regression analysis, hypothesis testing, and data mining. Experience with data visualization tools, such as Tableau, Power BI, or QlikView. Solid understanding of SQL for data manipulation and extraction. Familiarity with data warehousing concepts and database systems (e. g. , SQL Server, Oracle). Excellent analytical and problem - solving skills, with attention to detail. Strong communication and presentation skills, with the ability to effectively communicate complex data insights to non - technical stakeholders. Ability to work independently and collaboratively in a fast - paced environment, handling multiple projects and priorities.

· Design, develop, and deploy machine learning models for real-world applications. · Build and maintain scalable ML pipelines using tools like Airflow, MLflow, or Kubeflow. · Collaborate with data scientists, data engineers, and product teams to understand business needs and translate them into ML solutions. · Perform data preprocessing, feature engineering, and model evaluation. · Optimize model performance and ensure robustness, fairness, and explainability. · Monitor and maintain models in production, including retraining and performance tracking. · Contribute to the development of internal ML tools and frameworks. · Stay up to date with the latest research and best practices in machine learning and MLOps. Requirements · Strong working experience in Python · Hands on Experience in machine learning platforms, frameworks, and libraries · Strong understanding of Deep Learning concepts and conduct experiments and analyze results to optimize model performance and accuracy · Strong understanding of software engineering concepts to build robust and scalable AI systems. · Conceive, design, and develop NLP concepts (text representation, semantic extraction techniques and modeling) · Knowledge in building web apps/UI/Reporting using Python packages like PlotlyDash, Streamlit and Panel etc. with User Centric design is an advantage. · Familiarity with cloud-based AI/ML services Benefits · Competitive salary and performance-based bonuses. · Comprehensive insurance plans. · Collaborative and supportive work environment. · Chance to learn and grow with a talented team. · A positive and fun work environment. Show more Show less

Prescience Decision Solutions is looking for ML Engineer to join our dynamic team and embark on a rewarding career journey. We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The Machine Learning Engineer will be responsible for designing, developing, and deploying machine learning models to solve complex problems and enhance our products or services. The ideal candidate will have a strong background in machine learning algorithms, programming, and data analysis. Responsibilities : Problem Definition : Collaborate with cross - functional teams to define and understand business problems suitable for machine learning solutions. Translate business requirements into machine learning objectives. Data Exploration and Preparation : Analyze and preprocess large datasets to extract relevant features for model training. Address data quality issues and ensure data readiness for machine learning tasks. Model Development : Develop and implement machine learning models using state - of - the - art algorithms. Experiment with different models and approaches to achieve optimal performance. Training and Evaluation : Train machine learning models on diverse datasets and fine - tune hyperparameters. Evaluate model performance using appropriate metrics and iterate on improvements. Deployment : Deploy machine learning models into production environments. Collaborate with DevOps and IT teams to ensure smooth integration. Monitoring and Maintenance : Implement monitoring systems to track model performance in real - time. Regularly update and retrain models to adapt to evolving data patterns. Documentation : Document the entire machine learning development pipeline, from data preprocessing to model deployment. Create user guides and documentation for end - users and stakeholders. Collaboration : Collaborate with data scientists, software engineers, and domain experts to achieve project goals. Participate in cross - functional team meetings and knowledge - sharing sessions.

Prescience Decision Solutions is looking for Power Apps Developer to join our dynamic team and embark on a rewarding career journey. App Development : Designing, developing, and deploying custom business applications using Microsoft Power Apps. This involves creating user interfaces, defining data sources, and implementing logic and workflows. Canvas and Model - Driven Apps : Building both canvas apps (where design flexibility is high, and users can create the layout freely) and model - driven apps (more structured apps that use existing data models and components). Data Integration : Connecting Power Apps to various data sources, such as SharePoint, Microsoft 365, SQL Server, Dynamics 365, Excel, or other cloud - based and on - premises data sources. UI/UX Design : Creating user - friendly interfaces by designing screens, forms, and controls that align with user requirements and ensure a smooth user experience. Automation : Implementing automation and workflows using Power Automate (formerly Microsoft Flow) within Power Apps to streamline business processes and trigger actions based on specific events or data changes. Customization and Configuration : Customizing apps based on business needs, configuring security settings, roles, permissions, and ensuring scalability and performance of the applications. Testing and Debugging : Performing thorough testing of developed apps to identify and resolve bugs, ensuring functionality and reliability before deployment. Documentation and Training : Creating documentation, guidelines, and user manuals for developed apps and providing training or support to end - users. Integration with Power Platform : Collaborating with other Microsoft Power Platform components like Power BI (for analytics) and Power Automate (for workflows) to create comprehensive solutions. Understanding of Power Apps Ecosystem : Keeping up - to - date with new features, updates, and best practices within the Power Apps ecosystem.

Prescience Decision Solutions is looking for Ops Data Engineer to join our dynamic team and embark on a rewarding career journey. The Data Center Engineer (Operations) is responsible for the day - to - day management and maintenance of the data center infrastructure. This includes ensuring the availability, reliability, and performance of all data center equipment and systems. Key Responsibilities : Infrastructure Maintenance : Perform regular inspections and maintenance of data center hardware, including servers, storage systems, networking equipment, and other critical infrastructure components. Monitor and manage power and cooling systems to ensure optimal performance and energy efficiency. Conduct routine preventive maintenance to minimize the risk of equipment failure. Troubleshooting and Issue Resolution : Respond to and resolve hardware and software issues in a timely manner. Coordinate with relevant teams and vendors to address more complex technical problems. Implement solutions to enhance system performance and reliability. Capacity Planning : Monitor and analyze data center capacity to ensure it meets current and future demand. Collaborate with other teams to plan for and implement capacity upgrades as needed. Security and Compliance : Implement and enforce security policies and procedures to safeguard data center assets. Ensure compliance with industry standards and regulations related to data center operations. Documentation : Maintain accurate and up - to - date documentation for all data center equipment, configurations, and procedures. Create and update standard operating procedures (SOPs) for routine tasks. Collaboration : Work closely with other IT teams, including network engineers, system administrators, and security specialists, to achieve overall organizational goals. Participate in cross - functional projects related to data center infrastructure. Emergency Response : Be part of an on - call rotation to respond to and address data center emergencies and outages. Develop and follow incident response plans to minimize downtime. Vendor Management : Coordinate with vendors for equipment procurement, maintenance, and support. Evaluate vendor performance and make recommendations for improvements.

Prescience Decision Solutions is looking for Data Platform ops engineers to join our dynamic team and embark on a rewarding career journey. Responsibilities : Data Platform Design and Architecture : Collaborate with cross - functional teams, including data scientists, data engineers, and business stakeholders, to understand data requirements and design scalable data platforms and architectures that meet the organization's needs. Data Integration : Develop data integration pipelines to ingest data from various sources (databases, APIs, streaming data, etc. ) into the data platform, ensuring data quality and consistency. Data Storage and Management : Implement and manage data storage solutions such as databases (SQL and NoSQL), data lakes, data warehouses, and cloud - based storage systems to store and organize large volumes of structured and unstructured data. Data Processing : Design and optimize data processing workflows and batch/streaming data pipelines to transform, cleanse, and prepare data for downstream analysis and reporting. Data Security and Governance : Implement data security measures, access controls, and data governance policies to protect sensitive data and ensure compliance with relevant regulations (e. g. , GDPR, HIPAA). Performance Tuning and Optimization : Monitor and optimize the data platform's performance, identifying bottlenecks and implementing improvements to enhance system reliability and responsiveness. Cloud Infrastructure Management : If the organization operates in a cloud environment, manage and optimize cloud - based data infrastructure, leveraging services provided by cloud providers (e. g. , AWS, Azure, GCP). Automation and DevOps : Employ automation and DevOps practices to streamline data platform operations, configuration management, and deployment processes. Monitoring and Troubleshooting : Set up monitoring systems to proactively detect issues and promptly troubleshoot and resolve data platform - related incidents. Documentation and Knowledge Sharing : Maintain comprehensive documentation of the data platform's design, configuration, and operational procedures. Share knowledge and best practices with the team to foster a culture of continuous learning. Requirements : Bachelor's degree in Computer Science, Information Technology, or a related field. A Master's degree is a plus. Proven experience as a Data Platform Engineer or a similar role, demonstrating a strong understanding of data infrastructure, data integration, and data management. Proficiency in programming languages such as Python, Java, or Scala.

You will be responsible for designing, developing, and deploying machine learning models for real-world applications. Your main tasks will involve building and maintaining scalable ML pipelines using tools like Airflow, MLflow, or Kubeflow. Additionally, you will collaborate with data scientists, data engineers, and product teams to understand business needs and translate them into ML solutions. Data preprocessing, feature engineering, and model evaluation will be part of your routine to optimize model performance and ensure robustness, fairness, and explainability. Monitoring and maintaining models in production, including retraining and performance tracking, will also be essential. You will contribute to the development of internal ML tools and frameworks while staying up to date with the latest research and best practices in machine learning and MLOps. To excel in this role, you should have strong working experience in Python and hands-on experience in machine learning platforms, frameworks, and libraries. A deep understanding of Deep Learning concepts is crucial to conduct experiments and analyze results for optimizing model performance and accuracy. You must also possess a solid understanding of software engineering concepts to build robust and scalable AI systems. Additionally, you will be involved in conceiving, designing, and developing NLP concepts such as text representation, semantic extraction techniques, and modeling. Knowledge in building web apps/UI/Reporting using Python packages like PlotlyDash, Streamlit, and Panel with User-Centric design is considered advantageous. Familiarity with cloud-based AI/ML services is also desirable. In return, you will receive a competitive salary and performance-based bonuses, comprehensive insurance plans, and the opportunity to work in a collaborative and supportive environment. You will have the chance to learn and grow with a talented team while enjoying a positive and fun work environment.,

Prescience Decision Solutions is looking for Senior Data Analyst/Senior Business Analyst to join our dynamic team and embark on a rewarding career journey The Senior Data Analyst is responsible for analyzing large datasets, interpreting data, and providing actionable insights to support business decision-making They will work closely with cross-functional teams to identify data needs, design data collection methods, perform data analysis, and communicate findings to stakeholders The Senior Data Analyst plays a crucial role in driving data-driven strategies and improving overall business performance Key Responsibilities:Collect, clean, and transform large datasets from various sources to ensure data accuracy and integrity Analyze complex datasets using statistical techniques and data mining methods to identify trends, patterns, and insights Interpret and communicate findings to both technical and non-technical stakeholders through reports, visualizations, and presentations Collaborate with cross-functional teams to understand business requirements and develop data analysis plans to address specific objectives Develop and maintain data models, dashboards, and reports to provide ongoing performance metrics and KPIs Identify data quality issues, perform data validation, and implement data cleaning and data normalization processes Utilize data visualization tools (e g , Tableau, Power BI) to create interactive dashboards and visual representations of data Stay updated with industry trends, emerging technologies, and best practices in data analysis and data management Identify opportunities to optimize data collection, analysis, and reporting processes, and implement efficient and automated solutions Mentor and provide guidance to junior data analysts, fostering their professional growth and development Qualifications and Skills:Bachelor's degree in statistics, mathematics, computer science, or a related field A master's degree is a plus X years of experience as a Data Analyst, preferably in a senior or lead role Proficiency in statistical analysis tools such as R, Python, or SAS Strong knowledge of data analysis techniques, including regression analysis, hypothesis testing, and data mining Experience with data visualization tools, such as Tableau, Power BI, or QlikView Solid understanding of SQL for data manipulation and extraction Familiarity with data warehousing concepts and database systems (e g , SQL Server, Oracle) Excellent analytical and problem-solving skills, with attention to detail Strong communication and presentation skills, with the ability to effectively communicate complex data insights to non-technical stakeholders Ability to work independently and collaboratively in a fast-paced environment, handling multiple projects and priorities

Prescience Decision Solutions is looking for Sr Data Analyst (SQL) to join our dynamic team and embark on a rewarding career journey Managing master data, including creation, updates, and deletion. Managing users and user roles. Provide quality assurance of imported data, working with quality assurance analysts if necessary. Commissioning and decommissioning of data sets. Processing confidential data and information according to guidelines. Helping develop reports and analysis. Managing and designing the reporting environment, including data sources, security, and metadata. Supporting the data warehouse in identifying and revising reporting requirements. Supporting initiatives for data integrity and normalization. Assessing tests and implementing new or upgraded software and assisting with strategic decisions on new systems. Generating reports from single or multiple systems. Troubleshooting the reporting database environment and reports. Evaluating changes and updates to source production systems. Training end-users on new reports and dashboards. Providing technical expertise in data storage structures, data mining, and data cleansing.