Senior Data Scientist

Data Science & Machine Learning St.Petersburg, Poland


As a leader of the Data Science team, you will run the development of next-generation platforms for customers micro-segmentation, clusterization, behavior analysis, and prediction as well as building up new improved recommendation systems for the customers.

You will use your expertise to design data science models and frameworks, data processing pipelines, and lead efforts of the ML models productization.

You will use project management skills to manage the deliverables and ensure all stakeholder work is complete on time. You will also manage stakeholder communications and present your project across a wide spectrum of management levels.

Lead Data Scientist is supposed to handle complex problems independently and demonstrate analytical thinking. At this position, you should be able to make judgments and recommendations based on the analysis and interpretation of data. 

The position requires excellent communication skills and experience working directly with technical teams as well as with business stakeholders. Being able to present findings in a meaningful and clear way is a must.


  • Lead a team of skilled data scientists and data engineers 
  • Plan the R&D process to fit sprint goals as well as the project milestones.
  • Design a new solution architecture for customers clusterization, NLP, and prediction analysis.
  • Drive the collection, cleaning, processing, and analysis of new and existing data sources.
  • Lead ML models development using Python/Tensorflow/Keras/Spark stack.
  • Communicate with business stakeholders to clarify their requirements and present the teamwork results.
  • Learn & stay current on developments in one or more analytics domains: Optimization, Machine Learning, Deep Learning / AI, Simulation, etc.


  • Advanced degree (MS/PhD) in a relevant technical field (e.g., Computer Science, Mathematics, Applied Mathematics, Statistics, Operations Research) with 5+ years’ experience in related data science, analytics, and model building roles.
  • Strong practical knowledge of analytical techniques and methodologies such as machine learning (supervised and unsupervised techniques), segmentation, time series modeling, response modeling, lift modeling, survival analysis.
  • Experience with look-alike modeling and sequential-input models, RNNs (LSTM, GRU, etc.)
  • Experience with NLP and textual data analysis.
  • Strong working experience in Python, SQL and NoSQL DBs.
  • Practical skills in usage of big data technologies and tools including Hadoop, MapReduce, Hive, Spark.
  • Fluency in such technologies like Tensorflow, keras, scikit, gensim, stanfordNLP, PySpark.
  • Understanding of and experience with customer intelligence & marketing domains a plus.
  • Great communication and presentation skills. Proven ability to present progress made by the team to senior business management and the project stakeholders.
  • Familiarity with cloud ML Platforms (Google AI Platform, Amazon Sagemaker, MS Azure AI Platform) is a plus.
  • Experience in working across different global cultures is a plus.

We offer:

  • Opportunity to work on bleeding-edge projects
  • Work with a highly motivated and dedicated team
  • Very competitive salary
  • Flexible schedule
  • Medical insurance
  • Benefits program
  • Corporate social events
  • Professional development opportunities

Placement and Staffing Agencies need not apply.  We do not work with C2C at this time. At this moment, we are not able to process H1B transfers. Applicants with CPT and OPT visas are welcome to apply.

About Us:

Grid Dynamics is the engineering services company known for transformative, mission-critical cloud solutions for retail, finance and technology sectors.

We architected some of the busiest e-commerce services on the Internet and have never had an outage during the peak season.

Founded in 2006 and headquartered in San Ramon, California with offices throughout the US and Eastern Europe, we focus on big data analytics, omnichannel services, DevOps, and cloud enablement.