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Data Scientist (Finance & Accounting / Forecasting)
Стабильная международная компания с богатой историей, четко прописанные обязанности и современный стек технологий (Databricks, PySpark). Возможность удаленной работы и фокус на профессиональном росте делают вакансию очень привлекательной.
Сложность вакансии
Роль требует глубоких знаний в области временных рядов и финансовой аналитики, а также владения стеком Big Data (PySpark) и облачными платформами. Высокие требования к коммуникативным навыкам для объяснения сложных моделей бизнесу.
Анализ зарплаты
Предлагаемая позиция соответствует уровню Middle Data Scientist. В Индии (Мумбаи) и при удаленной работе на глобальный рынок, зарплаты для специалистов с опытом 3+ года и знанием PySpark/Cloud обычно находятся в диапазоне 1,800,000 - 3,000,000 INR в год.
Сопроводительное письмо
I am writing to express my strong interest in the Data Scientist position at Jensen Hughes. With over three years of experience in developing predictive models and a deep specialization in time series forecasting, I am confident in my ability to contribute to your finance and accounting analytics initiatives. My background in implementing SARIMA, Prophet, and XGBoost models aligns perfectly with your requirements for enhancing revenue forecasting accuracy.
Throughout my career, I have demonstrated a strong proficiency in Python, PySpark, and SQL, alongside a proven track record of translating complex statistical findings into actionable business insights for non-technical stakeholders. I am particularly drawn to Jensen Hughes' commitment to safety and innovation, and I am eager to apply my expertise in machine learning and data visualization to support your global operations from the Mumbai-based team.
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Присоединяйтесь к глобальной команде Jensen Hughes и используйте свои навыки в Data Science для трансформации финансовых прогнозов!
Описание вакансии
Company Overview
Throughout our worldwide network of experts, clients and communities, we are renowned for our leadership in fire protection engineering – a legacy of responsibility we have proudly upheld since 1939. Today, our expertise extends broadly across closely related security and risk-based fields – from accessibility consulting and risk analysis to process safety, forensic investigations, security risk consulting, emergency management, digital innovation and more.Our engineers and consultants collaborate to solve complex safety and security challenges, ensuring our clients can protect what matters most. For over 80 years, we have helped mitigate risks that threaten lives, property and reputations. Through technology, expertise and industry-leading research, weremain dedicated to our purpose of making our world safe, secure and resilient.At Jensen Hughes, we believe that creating and sustaining a culture of trust, integrity and professional growth starts with putting our people first. Our employees are our greatest strength, and we value the unique perspectives and talents they bring to our organization. Our wide range of Global Employee Networks connect people from across the organization, supporting career development and providing forums for individuals to share experiences on topics they're passionate about. Together, we are cultivating a connected culture where everyone has the opportunity to learn, grow and succeed together.
Overview – Role
We are seeking a skilled and motivated Data Scientist to join our team. The ideal candidate will leverage data science techniques to develop predictive models, generate insights, and support strategic decision-making, particularly in revenue forecasting and financial analytics.
While our India office is based in Mumbai , this role can be handled remotely and will be responsible for supporting global operations.
This role offers the chance to work in a fast-paced environment and advance your career within a supportive and diverse team
Key Responsibilities
- Apply statistical techniques (regression, distribution analysis, hypothesis testing) to derive insights from data and create advanced algorithms and statistical models such simulation, scenario analysis, and clustering
- Explain complex models (e.g., RandomForest, XGBoost, Prophet, SARIMA) in an accessible way to stakeholders
- Visualize and present data using tools such as Power BI, ggplot, and matplotlib
- Explore internal datasets to extract meaningful business insights and communicate results effectively and write efficient, reusable code for data improvement, manipulation, and analysis
- Manage project codebase using Git or equivalent version control systems
- Design scalable dashboards and analytical tools for central use
- Build strong collaborative relationships with stakeholders across departments to drive data-informed decision-making while also helping in the identification of opportunities for leveraging data to generate business insights
- Enable quick prototype creation for analytical solutions and develop predictive models and machine learning algorithms to analyze large datasets and identify trends
- Communicate analytical findings in clear, actionable terms for non-technical audiences
- Mine and analyze data to improve forecasting accuracy, optimize marketing techniques, and informed business strategies, developing and managing tools and processes for monitoring model performance and data accuracy
- Work cross-functionally to implement and evaluate model outcomes
Requirements and Qualifications
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or related technical field
- 3+ years of relevant experience in data science and analytics and adept in building and deploying time series models
- Familiarity with project management tools such as Jira along with experience in cloud platforms and services such as DataBricks or AWS
- Proficiency with version control systems such as BitBucket and Python programming
- Experience with big data frameworks such as PySpark along strong knowledge of data cleaning packages (pandas, numpy)
- Proficiency in machine learning libraries (statsmodels, prophet, mlflow, scikit-learn, pyspark.ml)
- Knowledge of statistical and data mining techniques such as GLM/regression, random forests, boosting, and text mining
- Competence in SQL and relational databases along with experience using visualization tools such as Power BI
- Strong communication and collaboration skills, with the ability to explain complex concepts to non-technical audiences
Why you should join Jensen Hughes
- Opportunity to grow within a supportive and collaborative team environment
- Access to training and development programs to enhance your payroll expertise
- Career advancement with an established framework is in place – clearly defining expectations and outlining opportunities for advancement
#LI-SR1
*Jensen Hughes is an Equal Opportunity Employer. Qualified candidates will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.*
At Jensen Hughes, we embrace innovation and understand that people are increasingly using artificial intelligence (AI) tools like ChatGPT and other generative platforms to learn, prepare and communicate. We have provided some guidelines regarding the responsible use of AI in the recruitment process. Please click here to review.
The security of your personal data is important to us. Jensen Hughes has implemented reasonable physical, technical, and administrative security standards to protect personal data from loss, misuse, alteration, or destruction. We protect your personal data against unauthorized access, use, or disclosure, using security technologies and procedures, such as encryption and limited access. Only authorized individuals may access your personal data for the purpose for which it was collected, and these individuals receive training about the importance of protecting personal data. Jensen Hughes is committed to compliance with all relevant data privacy laws in all areas where we do business, including, but not limited to, the GDPR and the CCPA. Additionally, our service providers are contractually bound to maintain the confidentiality of personal data and may not use the information for any unauthorized purpose.
\*Policy on use of 3rd party recruiting agency for direct placements
Jensen Hughes will occasionally augment a recruiting search through agencies for certain positions when business conditions warrant. Jensen Hughes will not accept resumes, inquiries or proposals from recruiting agencies as an acceptable method to consider a candidate. 3rd party recruiting agencies must sign a standard Jensen Hughes agreement after being evaluated and accepted by a Human Resources or Talent Acquisition manager, or member of the talent acquisition team. Hiring managers and employees of Jensen Hughes are not authorized to accept resumes, engage in fee-based searches through recruiting firms or sign a search agreement. Please note this policy does not apply to “staffing firms” or firms that are involved with hiring temporary staff. Any recruiting agency interested in being considered may contact our recruiting team at jensenhughesrecruiting.com.
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Навыки
- Python
- SQL
- PySpark
- Pandas
- NumPy
- Scikit-learn
- Prophet
- XGBoost
- Random Forest
- Power BI
- Git
- AWS
- Databricks
- MLflow
- Jira
- statsmodels
Возможные вопросы на собеседовании
Вакансия сфокусирована на прогнозировании выручки, где временные ряды являются ключевым инструментом.
Расскажите о вашем опыте работы с моделями Prophet или SARIMA: как вы обрабатываете сезонность и аномалии в финансовых данных?
В требованиях указан PySpark и работа с большими данными.
В каких ситуациях вы предпочтете использовать PySpark вместо стандартного Pandas для обработки данных, и с какими ограничениями вы сталкивались?
Роль предполагает тесное взаимодействие с финансовым отделом.
Как вы объясните нетехническому финансовому директору разницу между результатами модели случайного леса и линейной регрессии?
Упоминается использование MLflow и версионирования кода.
Опишите ваш типичный рабочий процесс MLOps: как вы отслеживаете эксперименты и обеспечиваете воспроизводимость моделей?
Финансовое прогнозирование требует высокой точности.
Какие метрики вы используете для оценки качества моделей прогнозирования и как вы боретесь с переобучением на зашумленных финансовых данных?
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