Data Science Engineer Job at Zessta

Data Science Engineer

Our client is a company that enables people, enterprises, and cities to harness ...

Location

Salary:

Not provided

Intellias

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Applied Mathematics, Operations Research, or a related field — or equivalent practical experience
3–5+ years of hands-on experience in data science, algorithm evaluation, ML model validation, or analytics within a product/engineering team
Strong Python proficiency for data engineering, analysis, scripting, and automation (comfortable with NumPy, Pandas, scikit-learn or equivalent)
Solid statistical foundations: hypothesis testing, confidence intervals, bias/variance trade-off, calibration, and A/B testing principles
Proven ability to design and implement end-to-end evaluation pipelines and translate results into actionable product requirements
Experience working with large datasets
familiarity with ETL/feature pipelines and batch or near-real-time data processing
Demonstrable experience building dashboards and monitoring systems to track model/algorithm quality and key performance indicators
Strong communication skills and the ability to present quantitative findings clearly to engineering and product stakeholders
Python for data analysis and automation (NumPy, Pandas, scikit-learn or equivalent)

Job Responsibility

Shift from classic test automation to data-driven evaluation and algorithm quality assurance
Build and maintain end-to-end evaluation pipelines for optimization outputs, define robust statistical quality metrics, and implement monitoring and alerting for production algorithms
Combine software engineering-in-test practices with deep data-analysis skills to validate complex optimization systems and ensure reliable, measurable product behavior
Work closely with engineering and product teams to operationalize validation, improve algorithm robustness, and drive continuous improvement of the Tour Planning product
Design, build, and maintain end-to-end evaluation pipelines for algorithmic outputs (ingest, transform, score, aggregate, visualize)
Define and own KPI-based validation frameworks for optimization performance (distance/cost reduction, SLA adherence, load balancing, constraint violations, solution feasibility)
Implement statistical and quantitative validation methods to assess algorithm quality
Develop dashboards and monitoring systems to track model/algorithm health, performance trends, and anomalies
create alerts for significant quality degradations
Perform root-cause analyses on detected issues: analyze SHAP/feature attributions, distribution shifts, data pipeline problems, and model behavior changes

Data Science Engineer

Location

India , Mumbai

Salary:

Not provided

NeoQuant Solutions Pvt Ltd

Expiration Date

Until further notice

Requirements

Bachelor’s degree in IT or Computers or related field
Strong foundational understanding in applied statistics
Extensive experience working on the areas of machine learning (ML) and artificial intelligence, deep learning, natural language processing, forecasting and other approaches to structured/unstructured data, advanced predictive modelling, visual analytics etc.
Significant coding experience in SQL/R and/or Python
Strong analytical and problem-solving skills to be able to structure and solve open ended business problems
Experience with practical implementation of emerging AI and ML research concepts highly preferred
Experience in deploying ML models to cloud (Azure/AWS)
Hands on experience in Python Flask application
4 Years to 6 Years experience

Fulltime

Data Science Engineer

At DevSavant, we are a trusted technology partner specializing in Software Devel...

Location

Salary:

Not provided

DevSavant Inc.

Expiration Date

Until further notice

Requirements

3-5+ years of work experience in software engineering, with a strong focus on data engineering, ML engineering, or building applications that use a lot of data
Expert in Python, with a strong understanding of object-oriented design, software system design, and experience building high-quality, testable code for production
Strong, hands-on experience with tools for handling large amounts of data like Apache Spark (PySpark), Dask, or similar
Solid experience with cloud platforms (GCP is highly preferred). This includes putting services live, managing them, making them handle more users (e.g., Docker, Cloud Run, GKE), and working with large data systems (e.g., Dataproc, BigQuery)
Strong SQL skills and experience working with large, complex datasets
Deep understanding of machine learning ideas, the full process of creating a model, and MLOps principles
Excellent problem-solver, good at fixing complex issues in systems that run on many computers, and making them perform better and handle more data
Explain complex technical ideas and system design decisions clearly and effectively in English
Advanced English proficiency (B2-C1)
Excellent communication, teamwork, and consulting skills

Job Responsibility

Design, develop, test, and maintain strong and scalable data pipelines using Python and tools for large-scale data processing (like Spark, Dask, or similar on GCP)
Design and take ownership of key parts of our ML systems, making sure they are reliable, efficient, and can grow
Set up and manage MLOps practices, including automatic updates for machine learning models (CI/CD), model monitoring, and automated launch plans
Improve and manage data processing jobs on cloud platforms (GCP: Dataproc, BigQuery, Cloud Run, Cloud Build)
Work with data scientists to get machine learning models ready for production and connect them to our data systems
Write detailed documents for the system designs, code, and systems you create and manage
Fix complex technical problems in data systems that run on many computers and in ML pipelines

Fulltime

Data Science Engineer

Softthink Solutions is seeking a highly motivated and result-oriented Data Scien...

Location

United States , Herndon

Salary:

Not provided

Softthink Solutions

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Computer Science, Computer Information Systems, Information Technology or a combination of education and experience equating to the U.S. equivalent of a Bachelor’s degree in one of the aforementioned subjects

Job Responsibility

Develop and maintain a demand forecasting model for a large volume of unique textbook SKUs, which serves as the basis for inventory management, pricing, and sales
Use a decision tree to develop a Quality scoring model, optimize for better results, and segment and rank inventory more effectively
Build pricing algorithms to optimize B2C sales and rental rebate, lead to an average margin increase of 10%
Develop Python scripts to scrape prices from various aggregator websites, enhance data collection and analysis capabilities
Build data pipelines to ingest, transform and clean data from diverse sources like Excel, text, JSON, and multiple databases from across the organization
Proficient in coding SQL queries, stored procedures, and building reports in Power BI and Tableau, as well as building and optimizing data warehouses, schemas, pipes, and tables in Snowflake
Develop and implement testing plans to ensure the accuracy and validity of models and algorithms, including unit testing, integration testing, and regression testing
Conduct A/B testing to measure the effectiveness of different pricing strategies and other business decisions and using statistical analysis to evaluate the results
Identify and address any issues or errors in the data or models, and work with other team members to develop solutions and improve performance
Create and maintain documentation for testing procedures and results, as well as for models, algorithms, and data pipelines

Fulltime

ML / Data Engineer – Data Science Enablement

This role will report to the Data Science Enablement Manager and support the Rar...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s in Computer Science, Data Engineering, or related technical field
3–5 years of experience in ML engineering, data engineering, or related roles
Strong programming skills in Python and SQL
Experience with data pipeline development and distributed computing (e.g., Spark/PySpark)
Working knowledge of Databricks and at least one cloud platform (AWS, Azure, or GCP)
Experience with ML lifecycle tools (e.g., MLflow, Git, CI/CD pipelines)
Understanding of model deployment, monitoring, and reproducibility practices

Job Responsibility

Build and maintain scalable data and ML pipelines to support patient finding use cases across the patient journey
Productionize machine learning models by developing deployment workflows, APIs, and batch/real-time scoring pipelines
Design and implement model evaluation, validation, and monitoring frameworks (performance tracking, drift detection, alerting)
Enable end-to-end ML lifecycle management, including training, versioning, deployment, and retraining workflows
Partner with RDBU data science teams to translate analytical solutions into production-ready systems
Develop ML-ready datasets and feature pipelines, ensuring data quality, consistency, and reusability
Support model tracking and experiment management using standardized tools and frameworks
Build tools and utilities to monitor, track, and operationalize model outputs for downstream consumption
Collaborate with enterprise data and platform teams to ensure compliance with data governance, security, and architecture standards
Follow engineering best practices for code quality, documentation, testing, and CI/CD integration

Senior Data Science Engineer

At T-Mobile Advertising Solutions, we're building privacy-first advertising prod...

Location

United States , Philadelphia; New York

Salary:

116500.00 - 210100.00 USD / Year

T-Mobile

Expiration Date

Until further notice

Requirements

Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience
Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.)
4-7 years experience building and deploying machine learning and deep learning solutions at scale
familiarity with MLOps and DevOps practices and tools
4-7 years Experience working within big data architecture, modern analytical data platforms, and large-scale data warehousing technologies (e.g. BigQuery, Snowflake, Redshift)
4-7 years Experience working with large-scale distributed data systems and cloud platforms (e.g. SQL, Python, Scala, AWS)
4-7 years Experience solving complex data, machine learning, or algorithmic challenges in production environment using modern engineering practices
At least 18 years of age
Legally authorized to work in the United States

Job Responsibility

Lead the end-to-end development of machine learning and data products aligned to business objectives, from problem framing through deployment and monitoring
Build scalable data, training, and inference pipelines using distributed processing and cloud technologies
Apply statistical methods, experimentation, and validation frameworks to ensure solution quality and business impact
Write production-quality code and contribute to engineering best practices, including testing, CI/CD, and observability
Collaborate across engineering, product, and business teams while leading other engineers and data scientists

What we offer

Competitive base salary
Annual stock grant
Employee stock purchase plan
401(k)
Free, year-round money coaches
Medical, dental and vision insurance
Flexible spending account
Paid time off and up to 12 paid holidays
Paid parental and family leave
Family building benefits

Fulltime

Backend Engineer (Data Science / ML)

Location

Finland , Helsinki

Salary:

Not provided

Zalando

Expiration Date

Until further notice

Requirements

Solid command of Kotlin, additional JVM based languages (Scala or Java), knowledge of software patterns and paradigms like continuous integration, test automation and deployment pipelines
Not only a strong command of Databricks with Apache Spark, but you are also comfortable taking the model from a notebook and wrapping it in a high-performance Kotlin microservice deployed on Kubernetes
You are a Backend Engineer at heart, but you possess a strong interest (or foundational experience) in Data Science, Applied AI, or Machine Learning
You enjoy working with large datasets and have a solid understanding of how data structures impact the performance of ML-driven applications
Experience in specifying, planning, developing, maintaining and operating microservices using REST API (OpenAPI), Cloud Platforms (AWS, Kubernetes), PostgreSQL
You have good communication and collaboration skills and enjoy working in an international and diverse environment with a positive no-job-is-beneath you attitude as a team player
You are self-motivated and have a proactive mindset with a passion for continuous improvement
You have problem-solving skills and ability to apply logical and analytical thinking to complex problems

Job Responsibility

Design and implement predictive delivery models using Databricks with Apache Spark, translating complex data into real-time backend insights
Take ownership of new features, take them from idea to technical design, and from technical design to cross system implementation
Help us to be a better team by continuously reflecting upon our ways of working and suggesting improvements
Actively participate in the entire product development lifecycle, from initial concept and design through to development, testing, deployment, and operation
Proactively identify and solve complex technical challenges, always approaching problems with a 'Partner First' mindset to deliver solutions that simplify their daily operations

What we offer

Culture of trust, empowerment and constructive feedback with internal guilds and Employee Resource Groups, knowledge sharing through tech talks and open source commitment, internal tech academy and blogs, product demos, meetups, parties and events
Competitive salary and employee shares program
40% Zalando discount of products sold and shipped by Zalando, 30% off Zalando Lounge and additional discounts from external partners
Monthly transport, lunch and recreation vouchers, private health insurance and occupational health care services, family services, free beverages and snacks, diverse sports and health offerings
Centrally located office in Kamppi, Helsinki, with flexible working times, additional holidays and hybrid working model
Extensive onboarding, mentoring and training opportunities and an international team of experts to work with

Fulltime

Platform Engineer - Data Science Platform

Location

United States , Columbus, OH or Dallas, TX or Minneapolis, MN

Salary:

Not provided

Robert Half

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science or a related field, or equivalent practical experience
5+ years of experience supporting Data Science infrastructure
5+ years of hands-on experience with AWS-hosted Data Lake, Data Science, or AI/ML platforms
5+ years of working knowledge with Kubernetes
AWS services such as SageMaker, Glue, Lambda, Athena
CI/CD tools such as Azure DevOps
Infrastructure as Code tools such as Terraform
Container technologies including Docker and Amazon ECR
Security tools such as AQUA and Kenna
Experience producing technical documentation and written solutions

Job Responsibility

Support and maintain ongoing Data Science infrastructure operations
Design, build, and deploy AWS environments using automated CI/CD pipelines
Manage and scale large, secure cloud environments to support current and future Data Science initiatives
Implement, own, and improve the image management lifecycle process
Assist with the setup and ongoing management of AWS accounts dedicated to the Data Science platform
Develop and maintain infrastructure pipelines using CI/CD tools (e.g., Azure DevOps)
Build and manage environments using Infrastructure as Code (IaC) tools such as Terraform
Develop scripts and applications using programming languages such as Python
Manage and support database technologies including Athena, Oracle, MySQL, and PostgreSQL
Leverage AWS services to enable Data Lake, Data Science, and AI/ML workloads

What we offer

medical
vision
dental
life and disability insurance
401(k) plan

Fulltime

Select Country

Data Science Engineer

Job Responsibility

Requirements

Looking for more opportunities?

Data Science Engineer

Data Science Engineer

Data Science Engineer

Data Science Engineer

Data Science Engineer

ML / Data Engineer – Data Science Enablement

Senior Data Science Engineer

Backend Engineer (Data Science / ML)

Platform Engineer - Data Science Platform

Our AI answers in your language