Mid-level Data Scientist
Lithuania - Vilnius
- Pay
EUR 3,800–4,800/month · Base · Gross — pay source
We offer a competitive, well-rounded rewards package crafted to support the financial, physical, and emotional well-being of our employees and their dependants. The base pay range for this role is 3800 – 4800 EUR gross monthly. Actual pay depends on your skills, experience, and qualifications. In addition to base pay, we offer short-term incentives (bonus or commission) and long-term incentives (equity), where applicable. Additional benefits include:
Read the full posting- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingYou'll work closely with cross-functional teams to deliver solutions that drive smarter decisions and measurable results.
Design, develop, and implement machine learning and AI solutions that create measurable value across the organization.
Partner with business and technology teams to understand challenges, find opportunities, and deliver data-driven solutions.
From the employer’s posting
As a Mid-level Data Scientist within the Core AI Development team, you'll play a role in developing innovative Machine Learning solutions, and helping build the future of our products, services, and client experiences! You'll thrive in this role if you're curious and ambitious professional who enjoys solving sophisticated problems, exploring new technologies, and translating data into business impact. You'll work closely with cross-functional teams to deliver solutions that drive smarter decisions and measurable results. Key Responsibilities
Key Responsibilities Design, develop, and implement machine learning and AI solutions that create measurable value across the organization. Transform complex data into actionable insights and recommendations for both technical and non-technical audience.
Transform complex data into actionable insights and recommendations for both technical and non-technical audience. Partner with business and technology teams to understand challenges, find opportunities, and deliver data-driven solutions. Communicate project progress, key findings, and business impact to partners at various levels of the organization.
What you’ll bring
All qualificationsCore experience
- Bachelor's degree or equivalent experience in Computer Science, Mathematics, Physics, Engineering, Statistics, Data Science, or a related quantitative field.
- 2-4 years of professional Data Scientist or Machine Learning Engineer experience.
- Strong understanding of Statistics, Machine Learning, and Deep Learning concepts, including hypothesis testing, regression, classification, optimization, and neural network architectures.
- Proficiency in Python and SQL, with experience working with large datasets and relational databases.
Preferred experience
- Experience working in financial services, Fintech, capital markets, or another data-driven and highly regulated industry.
- Hands-on experience building applications, solutions, or workflows using Generative AI.
- Practical experience developing, deploying, monitoring, and optimizing machine learning or deep learning models in production environments.
Qualification wording
Bachelor's degree or equivalent experience in Computer Science, Mathematics, Physics, Engineering, Statistics, Data Science, or a related quantitative field.
2-4 years of professional Data Scientist or Machine Learning Engineer experience.
Strong understanding of Statistics, Machine Learning, and Deep Learning concepts, including hypothesis testing, regression, classification, optimization, and neural network architectures.
Proficiency in Python and SQL, with experience working with large datasets and relational databases.
Experience working in financial services, Fintech, capital markets, or another data-driven and highly regulated industry.
Hands-on experience building applications, solutions, or workflows using Generative AI.
Practical experience developing, deploying, monitoring, and optimizing machine learning or deep learning models in production environments.
Tools in this posting
- Python
- SQL
Source — Tool mentions in context
- Strong understanding of Statistics, Machine Learning, and Deep Learning concepts, including hypothesis testing, regression, classification, optimization, and neural network architectures. - Proficiency in Python and SQL, with experience working with large datasets and relational databases. - Strong verbal and written English communication skills, with the ability to explain sophisticated concepts and collaborate optimally across cross-functional teams.
Job description
As a Mid-level Data Scientist within the Core AI Development team, you'll play a role in developing innovative Machine Learning solutions, and helping build the future of our products, services, and client experiences!
You'll thrive in this role if you're curious and ambitious professional who enjoys solving sophisticated problems, exploring new technologies, and translating data into business impact. You'll work closely with cross-functional teams to deliver solutions that drive smarter decisions and measurable results.
Key Responsibilities
- Design, develop, and implement machine learning and AI solutions that create measurable value across the organization.
- Transform complex data into actionable insights and recommendations for both technical and non-technical audience.
- Partner with business and technology teams to understand challenges, find opportunities, and deliver data-driven solutions.
- Communicate project progress, key findings, and business impact to partners at various levels of the organization.
Required Qualifications
- Bachelor's degree or equivalent experience in Computer Science, Mathematics, Physics, Engineering, Statistics, Data Science, or a related quantitative field.
- 2-4 years of professional Data Scientist or Machine Learning Engineer experience.
- Strong understanding of Statistics, Machine Learning, and Deep Learning concepts, including hypothesis testing, regression, classification, optimization, and neural network architectures.
- Proficiency in Python and SQL, with experience working with large datasets and relational databases.
- Strong verbal and written English communication skills, with the ability to explain sophisticated concepts and collaborate optimally across cross-functional teams.
Preferred Qualifications
- Experience working in financial services, Fintech, capital markets, or another data-driven and highly regulated industry.
- Hands-on experience building applications, solutions, or workflows using Generative AI.
- Practical experience developing, deploying, monitoring, and optimizing machine learning or deep learning models in production environments.
This position is located in Vilnius, Lithuania and offers the opportunity for a hybrid work environment with at least 3 days per week in-office.
Note: The candidate is encouraged to moderately align their schedule with US East Coast working hours (10 AM – 7 PM EET/EEST).
Benefits & Rewards
We offer a competitive, well-rounded rewards package crafted to support the financial, physical, and emotional well-being of our employees and their dependants.
The base pay range for this role is 3800 – 4800 EUR gross monthly. Actual pay depends on your skills, experience, and qualifications. In addition to base pay, we offer short-term incentives (bonus or commission) and long-term incentives (equity), where applicable.
Additional benefits include:
- Employee Stock Purchase Plan with discounted company shares
- Pension plan with Nasdaq contribution
- 6 additional days off per year
- Work from (almost) anywhere - up to 20 days per year
- Paid time off to volunteer
- Health insurance
- Free gym, yoga, and pilates classes, plus discounted in-office massages
- 24/7 mental health support for you and your family
- Global mentoring program
- Unlimited access to e-learning platforms
- Modern, comfortable office environment with fresh fruit, snacks, and weekly Fika breaks
We apply a structured job architecture and career framework to ensure growth opportunities are clear, fair, and accessible to all employees. The pay range reflects the full salary band for this job level, including room for progression over time.
For more information, visit Nasdaq Benefits & Rewards Career Page.
Individuals applying for or occupying this position must have no previous unspent convictions for criminal offences under the Criminal Code of the Republic of Lithuania, with the exception of offences solely related to minor road traffic violations.
Come as You Are
Nasdaq is an equal opportunity employer. We welcome applications from candidates of all backgrounds and identities.
We are committed to fostering an inclusive workplace where diverse perspectives, experiences, and identities are valued and celebrated.
We ensure that individuals with disabilities are provided with reasonable accommodation throughout the hiring process.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on nasdaq.wd1.myworkdayjobs.com. The employer’s form will show what is required.
Already applied? Track this application
Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
We offer a competitive, well-rounded rewards package crafted to support the financial, physical, and emotional well-being of our employees and their dependants. The base pay range for this role is 3800 – 4800 EUR gross monthly. Actual pay depends on your skills, experience, and qualifications. In addition to base pay, we offer short-term incentives (bonus or commission) and long-term incentives (equity), where applicable. Additional benefits include:
- Location & working pattern
Lithuania - Vilnius
- Practical experience developing, deploying, monitoring, and optimizing machine learning or deep learning models in production environments. This position is located in Vilnius, Lithuania and offers the opportunity for a hybrid work environment with at least 3 days per week in-office. Note: The candidate is encouraged to moderately align their schedule with US East Coast working hours (10 AM – 7 PM EET/EEST).
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jun 2, 2026
- Recorded sightings
- 74
- Last seen by us
- Oct 8, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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