37 Senior Data Scientist Galway Ireland jobs in Ireland

Why PlayStation?

PlayStation isn't just the Best Place to Play - it's also the Best Place to Work. Today, we're recognized as a global leader in entertainment producing The PlayStation family of products and services including PlayStation5, PlayStation4, PlayStationVR, PlayStationPlus, acclaimed PlayStation software titles from PlayStation Studios, and more.

PlayStation also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team.

The PlayStation brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Group Corporation.

Mid-Level Machine Learning Engineer - Pricing

Do you want to join a Machine Learning team committed to enhancing the PlayStation experience for hundreds of millions of users and also game studios? The work we do delivers highly impactful pricing recommendations to our studios and has strong leadership sponsorship. The Machine Learning Engineers within the DTIS group will deliver optimized interactions across PlayStation experiences by designing, coding, training, documenting, cost-effectively deploying, and evaluating business-critical machine learning and AI systems.

We are looking for someone who can architect and build delightful production-grade products for customer-facing experiences, in an agile environment, collaborating with teams across Engineering, Product and Business. You will work on a project backed by executive leadership and poised to significantly influence revenue and user engagement.
You Will:
• Build and maintain ML models that quantify product price-elasticity and cannibalization effect to support multi-period promotions.
• Refine time-series forecasting algorithms to predict demand across multiple regions and product lines.
• Develop optimization workflows (OR-Tools) that balance sales growth and business constraints.
• Refine clustering algorithms to identify lookalike products for smarter pricing and promotional strategies.
• Apply a broad spectrum of state-of-the-art machine learning and deep learning technologies in the areas of classification, regression, clustering, time series forecasting, uplift modeling, and synthetic data generation.
• Build scalable and resilient ML systems along with appropriate monitoring and continuous evaluation frameworks.
• Work closely with cross-functional partners in business and product to translate requirements into effective, scalable, ML-driven solutions.
• Collaborate with other engineering functions in Client, Server, and QA to drive ML integrations and deliver results.
• Collaborate with ML application teams that power product personalizations and search to further enhance the core experiences of our players.
You Bring:
• Advanced degree (Master's or Ph.D.) in CS/Statistics/Data Science/Operations Research/Econometrics, specializing in machine learning and optimization problems.
• 1+ years of industry experience applying time-series models in production, with hands-on experience in forecasting libraries (e.g. with LightGBM, Prophet).
• Proven track record with mixed-integer programming or constraint solvers for pricing or resource allocation.
• Strong programming skills in Python, Java, with proficiency in ML libraries and frameworks like TensorFlow, PyTorch, Spark Mlib, and scikit-learn
• Good ML systems engineering experience (such as job orchestration, training pipelines, deployment, serving, monitoring).
• Expertise in measuring the performance unsupervised and supervised models.
• Proven record of successfully delivering commercial machine learning products from conception to production.
• Experience with software engineering principles, modern ML tech stacks, and use of Databricks, Tecton, Snowflake, and cloud services like AWS for machine learning development and deployment.
Preferred Qualifications:
• Previously worked with revenue-management systems.
• Experience in a variety of machine learning and AI techniques, such as forecasting models, constraint optimization, classification models on structured data, clustering, and other supervised and unsupervised learning models.
• Experience working in fast-paced environments, on business-critical missions.
• Good communication skills and the ability to convey complex ML concepts to a non-ML audience.
• Experience in e-commerce, digital goods, or gaming industries.
• Experience with recommender systems and similarity matching algorithms.
• Background in experimentation design, causal inference, uplift modeling, online A/B testing frameworks, and relevant metrics.
• Experience with large-scale structured data manipulation and processing.
• Experience working with custom ML platforms for continuous integration, deployment, and monitoring of machine learning models.

Equal Opportunity Statement:

Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.

We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.

PlayStation is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Company:

Sony Interactive Entertainment (SIE)

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Industry, Ireland, NLP, QA, Supervised Learning, Unsupervised Learning

Sony Interactive Entertainment (SIE)

Senior (5+ years of experience)

Tagged as: Classification , Industry , Ireland , NLP , QA , Recommendation System

Intercom is the AI Customer Service company on a mission to help businesses provide incredible customer experiences.

Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better. Fin can also be combined with our Helpdesk to become a complete solution called the Intercom Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent.

Founded in 2011 and trusted by nearly 30,000 global businesses, Intercom is setting the new standard for customer service. Driven by our core values, we push boundaries, build with speed and intensity, and consistently deliver incredible value to our customers.

Intercom's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers' hands.

We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.

Identify areas where ML can create value for our customers

Identify the right ML framing of product problems

Working with teammates and Product and Design stakeholders

Conduct exploratory data analysis and research

Deeply understand the problem area

Research and identify the right algorithms and tools

Being pragmatic, but innovating right to the cutting-edge when needed

Perform offline evaluation to gather evidence an algorithm will work

Work with engineers to bring prototypes to production

Plan, measure & socialize learnings to inform iteration

Partner deeply with the rest of team, and others, to build excellent ML products

Broad applied machine learning knowledge

3-5 years applied ML experience

Practical stats knowledge (experiment design, dealing with confounding etc)

Strong communication skills, both within engineering teams and across disciplines.

Comfort with ambiguity

Typically have advanced education in ML or related field (e.g. MSc)

Scientific thinking skills

Track record shipping ML products

PhD or other experience in a research environment

Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering

Strong stats or math background

We are a well treated bunch, with awesome benefits! If there's something important to you that's not on this list, talk to us!

Competitive salary and equity in a fast-growing start-up

We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen

• Pension scheme & match up to 4%

Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents

Flexible paid time off policy

Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones

If you're cycling, we've got you covered on the Cycle-to-Work Scheme. With secure bike storage too

MacBooks are our standard, but we're happy to get you whatever equipment helps you get your job done

• Relocation support for those moving to our offices

Intercom has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

We have a radically open and accepting culture at Intercom. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values .

Intercom values diversity and is committed to a policy of Equal Employment Opportunity. Intercom will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.

Interested in building your career at Intercom? Get future opportunities sent straight to your email.

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Intercom's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers' hands.

We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.

• Identify areas where ML can create value for our customers

• Identify the right ML framing of product problems

• Working with teammates and Product and Design stakeholders

• Conduct exploratory data analysis and research

• Deeply understand the problem area

• Research and identify the right algorithms and tools

• Being pragmatic, but innovating right to the cutting-edge when needed

• Perform offline evaluation to gather evidence an algorithm will work

• Work with engineers to bring prototypes to production

• Plan, measure & socialize learnings to inform iteration

• Partner deeply with the rest of team, and others, to build excellent ML products

• Broad applied machine learning knowledge

• 3-5 years applied ML experience

• Practical stats knowledge (experiment design, dealing with confounding etc)

• Intermediate programming skills

• Strong communication skills, both within engineering teams and across disciplines.

• Comfort with ambiguity

• Typically have advanced education in ML or related field (e.g. MSc)

• Scientific thinking skills

• Track record shipping ML products

• PhD or other experience in a research environment

• Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering

• Strong stats or math background

• Visualization, data skills, SQL, matplotlib, etc.

We are a well treated bunch, with awesome benefits! If there's something important to you that's not on this list, talk to us!

• Competitive salary and equity in a fast-growing start-up

• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen

• Regular compensation reviews - we reward great work!

• Pension scheme & match up to 4%

• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents

• Flexible paid time off policy

• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones

• If you're cycling, we've got you covered on the Cycle-to-Work Scheme. With secure bike storage too

• MacBooks are our standard, but we're happy to get you whatever equipment helps you get your job done

• Relocation support for those moving to our offices