Senior Data Scientist (Advanced Analytics)

SoftServe; Town of Poland (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

SoftServe is seeking a skilled ML Engineer to design and deploy classical ML solutions within the AI and Data Science Center of Excellence. You will transform complex tabular and time-series data into production-ready models that drive operational efficiency.

Join a team of 170+ experts and collaborate with stakeholders to deliver forecasting, optimization, and dynamic scheduling use cases, with opportunities to explore Generative AI intersections across the AI spectrum.

Qualifications

• Master's or PhD in relevant field required.
• Strong foundation in time series and statistical methods.
• Experience deploying ML models to cloud platforms.
• Ability to translate business needs into ML solutions.

Responsibilities

• Design time series forecasting models (ARIMA, Prophet) for demand planning.
• Build end-to-end ML pipelines for tabular data from ingestion to production deployment.
• Collaborate with stakeholders to translate challenges into scalable ML solutions.
• Develop optimization and dynamic scheduling using OR-Tools or PuLP.
• Apply statistical methods to uncover actionable insights.
• Establish monitoring and retraining for production models.
• Document methodologies and results for technical and non-technical audiences.

Skills

Forecasting

Statistical analysis

Python programming

Data pipelines

Model deployment

Communication

English (fluid)

Education

Master's or Ph.D. in CS/Math/Stats/OR

Tools

scikit-learn

XGBoost

LightGBM

statsmodels

Prophet

OR-Tools

PuLP

AWS/GCP/Azure

Job description

About The Role

In this role, you will design and deploy classical machine learning solutions — from time series forecasting and predictive modelling to optimization and dynamic scheduling systems — within SoftServe's AI and Data Science Center of Excellence, a team of 170+ experts, including Data Scientists, ML Engineers, and Architects.

In this role, you will design and deploy classical machine learning solutions — from time series forecasting and predictive modelling to optimization and dynamic scheduling systems — within SoftServe's AI and Data Science Center of Excellence, a team of 170+ experts, including Data Scientists, ML Engineers, and Architects.

You’ll work closely with clients to transform complex tabular and temporal data into production-ready models that drive operational efficiency and measurable business outcomes. As part of the CoE, you’ll also have the opportunity to explore intersections with Generative AI and agentic systems, expanding your impact across the full AI spectrum.

Responsibilities

• Design and develop time series forecasting models — using techniques such as ARIMA, Prophet, or gradient boosting — to support demand prediction, trend analysis, and business planning
• Build end-to-end ML pipelines for tabular data, covering data ingestion, feature engineering, model training, validation, and production deployment on cloud platforms
• Collaborate with business stakeholders and domain experts to translate operational challenges into scalable ML solutions for forecasting, scheduling, and optimization use cases
• Develop mathematical optimization and dynamic scheduling solutions using frameworks such as OR-Tools or PuLP to automate complex resource allocation and planning problems
• Apply statistical analysis and predictive modelling techniques to uncover patterns in structured and time-dependent data, generating actionable insights for decision-makers
• Establish and maintain model monitoring, retraining pipelines, and performance evaluation frameworks to ensure ongoing reliability in production
• Document methodologies, model performance, and findings, communicating results clearly to both technical teams and non-technical stakeholders

Requirements

• Advanced Python proficiency with hands‑on experience in scikit-learn, XGBoost, LightGBM, statsmodels, and Prophet for tabular and time series modelling
• Strong knowledge of time series forecasting techniques
• Solid experience with mathematical optimization and dynamic scheduling frameworks such as OR-Tools or PuLP
• Strong statistical foundation, with practical knowledge of hypothesis testing, regression analysis, and causal inference methods
• Proven proficiency in working with structured and tabular data, including advanced feature engineering, preprocessing, and handling of temporal dependencies
• Hands‑on experience deploying ML models to cloud platforms (AWS, GCP, or Azure) and maintaining production-ready pipelines
• Master's or Ph.D. degree in Computer Science, Mathematics, Statistics, Operations Research, or a related field
• Strong analytical and communication skills, with the ability to present complex findings clearly to non-technical stakeholders
• Upper-intermediate or higher proficiency in English, both spoken and written

SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.