Data Scientist

JOB TITLE: Data Scientist

JOB STATUS: Regular, full-time

DEPARTMENT: Product Management

REPORTS TO: Director of Product Management

About Vista Equity Partners

Vista Equity Partners is a leading global investment firm focused exclusively on enterprise software, data, and technology-enabled businesses. With over $100B in assets under management and a portfolio of 90+ software product companies worldwide, Vista accelerates growth through operational excellence, shared expertise, and long-term partnership. In India, Vista’s presence continues to expand with 45+ portfolio companies employing more than 17,000 professionals across technology, product, customer success, and operations — reinforcing India’s strategic role as a hub of innovation and talent within the Vista ecosystem.

Through its Agentic AI Factory, Vista is embedding Generative AI across its global portfolio — enabling companies to integrate intelligent, responsible AI into products, operations, and decision-making. This initiative is strengthened through portfolio-wide learning programs, leadership workshops, and AI hackathons that foster innovation, build fluency, and accelerate practical AI adoption across teams.

About Amtech

Amtech is a leading provider of enterprise software solutions for the packaging, printing, and manufacturing industries. Our integrated systems streamline order management, production planning, scheduling, inventory, and business analytics — empowering customers to drive efficiency, reduce costs, and improve operational performance. With a strong commitment to innovation and customer success, Amtech delivers reliable technology backed by deep industry expertise.

With Vista’s investment and strategic guidance, we combine the agility of a growing technology organization with the scale, stability, and career mobility of a global software ecosystem.

Role Description

Amtech LLC is seeking a data scientist who is a machine learning and data expert that can research, prototype, and operationalize AI/ML models that enable intelligent features across manufacturing execution systems and ERP platforms. Focus areas include personalization of user workflows, predictive recommendations for operations and resources, and advanced analytics to optimize production efficiency, quality, and supply chain integration.

KEY RESPONSIBILITIES

Data analysis and feature engineering

• Analyze MES and ERP operational data to uncover patterns in production, machine performance, workforce productivity, and supply chain flow.

• Develop engineered features to improve model accuracy, e.g., cycle times, quality defect rates, energy consumption.

Model development and deployment

• Build ML models for personalization and recommendations (e.g., dynamic work instructions, task prioritization, supply ordering).

• Develop predictive models for equipment maintenance, demand forecasting, and production scheduling.

• Partner with ML engineers to deploy models into MES/ERP workflows at scale.

Operational optimization

• Deliver insights and models to improve throughput, reduce downtime, optimize labor and materials usage, and support real-time decision-making.

• Leverage reinforcement learning and optimization algorithms for production planning and scheduling.

Collaboration with cross-functional teams

• Partner with manufacturing engineers, operations leaders, and ERP/MES product managers to align ML capabilities with business outcomes.

• Work closely with data engineers to ensure data quality, integration from IoT/ERP sources, and pipeline scalability.

Data-driven insights and reporting

• Generate recommendations for continuous improvement in production and supply chain performance.

• Provide reporting and dashboards on KPIs such as yield, scrap rate, OEE, downtime, and forecast accuracy.

SKILLS & QUALIFICATIONS

Education

• Bachelor’s degree in Computer Science, Industrial Engineering, or Software Engineering.

• Advanced degree (Master’s or Ph.D.) in Machine Learning, Data Science, Operations Research, or related field is highly beneficial.

Statistical analysis and data modeling

• Strong knowledge of statistics, hypothesis testing, forecasting, and stochastic modeling.

• Experience with regression, clustering, classification, time-series, and optimization methods.

Machine learning and applied AI

• Proficiency in machine learning techniques for personalization, recommendation, anomaly detection, and predictive maintenance.

• Familiarity with deep learning frameworks (TensorFlow, PyTorch) and ML libraries (scikit-learn, XGBoost, LightGBM).

• Exposure to optimization techniques and reinforcement learning for scheduling, planning, and resource allocation.

Programming and data manipulation

• Proficiency in Python (or R) with strong use of Pandas, NumPy, SciPy.

• SQL for data extraction and transformation.

• Familiarity with cloud data platforms (AWS Redshift, Snowflake, BigQuery) and big data tools (Spark, Databricks, Hadoop).

Experimentation and validation

• Experience designing controlled experiments and evaluating ML models with domain-appropriate KPIs (e.g., throughput, yield, OEE, downtime reduction, cost savings).

Communication and visualization

• Strong ability to translate technical results into actionable insights for manufacturing leaders.

• Experience with visualization and BI tools (Tableau, Power BI, Sigma, or Matplotlib).

PREFERRED QUALIFICATIONS

Manufacturing and ERP data expertise

• Ability to model and analyze large-scale production, quality, and supply chain datasets.

• Knowledge of MES/ERP data domains such as work orders, bills of materials, machine telemetry, quality records, and inventory.

• Experience with IoT/sensor data integration and streaming analytics.

Why Join Amtech

At Amtech, you will drive meaningful financial impact in a growing enterprise software organization while benefiting from Vista’s world-class ecosystem. You’ll collaborate with talented peers, leverage cross-portfolio learning programs, and help shape the future of Amtech’s financial operations and systems. Build your career with Amtech — backed by the strength, scale, and innovation culture of Vista.