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project44
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SeniorГибридПолная занятость

Sr Analyst, Data Science

Оценка ИИ

Интересная позиция в быстрорастущей логистической компании с фокусом на передовые технологии (AI, агенты). Хорошие возможности для профессионального роста, хотя требуется работа из офиса 3 дня в неделю.


Вакансия из Quick Offer Global, списка международных компаний
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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует глубоких знаний как в продуктовой аналитике, так и в специфике машинного обучения (оценка моделей, обратные связи). Необходим опыт работы с современным стеком данных и понимание концепций AI-native аналитики.

Анализ зарплаты

Медиана45 000 $
Рынок35 000 $ – 60 000 $
Оценка ИИ

Зарплата для Senior Data Science ролей в Бангалоре в международных продуктовых компаниях обычно выше среднего по рынку. Указанный диапазон отражает текущие реалии для специалистов с опытом 4-6 лет в технологическом секторе Индии.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Analyst, Data Science position at project44. With over 5 years of experience in product analytics and a deep understanding of ML-powered systems, I am excited by the opportunity to bridge the gap between model performance and business outcomes for your Movement platform. My background in establishing evaluation frameworks for predictive models and my proficiency in SQL and Python align perfectly with your mission to redefine global supply chains.

In my previous roles, I have successfully translated complex product challenges into structured analytical frameworks and built scalable data foundations using dbt and Snowflake. I am particularly drawn to project44’s vision for AI-native and agent-driven analytics. I am eager to bring my expertise in causal inference and experimentation to help your team build autonomous insight generation systems that drive decisive action in the logistics space.

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Описание вакансии

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, *Movement*, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Sr Analyst, Data Science to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

  • We are looking for a Senior Product Analyst, Data Science, to drive analytics for ML-powered products at project44.
  • This role sits at the intersection of Product, Data Science, and Operations, with a mandate to define how ML systems are measured, evaluated, and improved in production. You will own the analytical frameworks that connect model performance to product outcomes, ensuring our AI capabilities deliver measurable business impact.
  • You will work on ambiguous, high-impact problems, designing experiments, evaluating models (offline and online), and shaping product strategy through data. This is not a reporting role. You are expected to operate as a thought partner to Product and Data Science, influencing decisions and driving outcomes.
  • As analytics evolves, this role will focus on building AI-native and agent-driven analytics systems, including semantic layers, data contexts, and automated insight generation. You will help define how analytics is consumed in an environment where agents, not just dashboards, drive decisions.

What You’ll Do

Own Product & ML Measurement

  • Define and operationalize success metrics across product and ML systems, including north-star metrics, product KPIs, and model-level evaluation frameworks.

Drive Model Evaluation & Feedback Loops

  • Evaluate model performance using offline and online metrics (e.g., precision/recall, lift, latency, adoption) and establish feedback loops to continuously improve models in production.

Translate Product Problems into Analytical Frameworks

  • Break down ambiguous product and operational problems into structured analyses that drive clear, actionable decisions.

Partner Across Product & Data Science

  • Work closely with Product Managers and Data Scientists to shape roadmaps, guide prioritization, and ensure alignment between model performance and user impact.

Build Scalable Analytics Foundations

  • Develop reusable datasets (SSOTs, data marts) and enable self-serve analytics across teams.

Build AI-Native Analytics Systems

  • Design and develop semantic layers, data models, and context systems that enable agent-driven analytics. Build and operationalize workflows where agents autonomously generate insights, monitor performance, and surface recommendations on a recurring basis.

Design Agent-Driven Analytics Workflows

  • Design and implement agent-driven analytics workflows where insights are generated, monitored, and delivered autonomously using LLMs and modern AI tooling.

What We’re Looking For

4–6+ years in Product Analytics, Data Science, or related roles, with experience supporting data-driven product decisions.

Analytical & Statistical Expertise

Strong foundation in statistics and experimentation, including hypothesis testing, A/B testing, and causal inference.

Technical Skills

Proficiency in SQL and Python, with experience working with large-scale, event-level datasets and modern data platforms.

ML Product Understanding

Experience defining and analyzing model performance metrics and understanding trade-offs between offline and online evaluation.

Cross-Functional Collaboration

Proven ability to work closely with Product and Data Science teams to drive outcomes.

Communication & Influence

Ability to clearly communicate complex analyses and influence stakeholders across technical and non-technical audiences.

Preferred Skills

  • Experience working on ML-powered products or data platforms
  • Familiarity with model evaluation concepts (precision/recall, ROC, calibration, bias/variance)
  • Experience analyzing online vs offline performance and feedback loops
  • Familiarity with modern data stack (dbt, Snowflake/BigQuery, event tracking, feature stores)
  • Experience with predictive modeling or close collaboration with Data Science teams
  • Hands-on experience using AI tools (LLMs, copilots) in analytical workflows
  • Experience building or working with agent-based or AI-native analytics workflows
  • Familiarity with semantic layers, metrics layers, or data context systems
  • Experience using LLMs for automated analysis, insight generation, or decision support
  • Strong product and business intuition

What Success Looks Like (6–12 Months)

  • Establish clear measurement frameworks for assigned ML-powered products
  • Improve visibility into model performance and diagnostics (offline and online)
  • Deliver actionable insights that influence product roadmap decisions for assigned products
  • Build scalable datasets and frameworks that enable self-serve analytics
  • Enable tighter feedback loops between Product, Data Science, and real-world outcomes

In-office Commitment:This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences.

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Навыки

  • A/B Testing
  • Python
  • Machine Learning
  • LLM
  • SQL
  • dbt
  • Statistics
  • BigQuery
  • Snowflake
  • Data Modeling
  • Causal Inference

Возможные вопросы на собеседовании

Проверка понимания специфики ML-продуктов и умения связывать технические метрики с бизнесом.

Как бы вы разработали систему метрик для оценки влияния точности ML-модели на конечный пользовательский опыт в логистической платформе?

Оценка навыков работы с данными и инструментами.

Опишите ваш опыт проектирования семантических слоев или витрин данных для самообслуживания (self-serve analytics). Какие инструменты вы использовали?

Проверка статистической грамотности.

Расскажите о случае, когда результаты A/B теста были неоднозначными. Как вы использовали причинно-следственный вывод (causal inference) для принятия решения?

Оценка готовности к работе с новыми технологиями (LLM).

Как, по вашему мнению, LLM и ИИ-агенты изменят процесс потребления аналитики в ближайшие годы, и как это отразится на архитектуре данных?

Проверка навыков коммуникации и влияния.

Приведите пример, когда ваши аналитические выводы заставили команду изменить приоритеты в дорожной карте продукта. Как вы убеждали стейкхолдеров?

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