数据科学家岗位职责

岗位职责：
1.负责轨交智能运维相关的数据分析工作；
2.负责轨交智能运维核心算法的研发工作；
3.负责支撑智能运维产品解决方案，明确边缘端数据采集需求和平台端的数据处理需求；
4.带领算法工程师完成智能运维算法部署工作；
5.根据客户需求及使用反馈，对智能运维核心算法进行迭代优化。
任职要求：
精通异常检测问题的数学建模与数据分析方法；
精通机器学习算法；
精通设备可靠性分析建模方法；
精通信号处理或贝叶斯网络故障诊断方法。

YOUR TASKS RESPONSIBILITIES
Creates, employs, evaluates, optimizes, maintains generative AI, machine learning, time series forecasting, mathematical optimization, simulation, NLP models workflows that deliver actionable insights meet business objectives.
Participates in the development, delivery, maintenance of a Generative AI Platform by implementing proposing new features, designing evaluation experiments, researching the latest advancements in the GenAI field.
Extracts valuable information from large structured unstructured datasets, identifying key variables metrics that influence consumer behavior, commercial activities, product supply, R&D RMSQC.
Builds prototypes to validate modeling concepts.
Industrializes scales up successful advanced analytics prototypes IT products.
Creates intuitive interactive data visualizations, reporting tools dashboards to communicate complex analytical findings to both technical non‑technical stakeholders, to support scenario creation management.
Develops generalized frameworks libraries frepetitive data science activities.
Participates in exploratory projects that investigate new data sources, tools, analytical techniques to keep Bayer at the forefront of data science in the consumer health sector.
Builds data processing pipelines, analyzes data used fmodeling, performs other data‑related activities as required.
Manages code in GitHub repositories performs peer code reviews.
Fosters a culture of continuous learning within the data science team by actively participating in workshops training sessions to share knowledge skills.
Presents compelling data‑driven stories to all levels of theganization—including peers, senimanagement, internal customers—to drive both strategic operational business decisions.
Acts as a subject matter expert in data science, advising on best practices emerging technologies that can enhance Bayer Consumer Health’s data science capabilities.
WHO YOU ARE
Master’s PhD degree with 3+ years of experience in Data Science related fields.
Proven educational background applied experience in at least one of the following: Machine Learning, Statistics, Mathematics, Computer Science, Quantitative Finance/Economics/Marketing, Biostatistics, Bioinformatics, other quantitative disciplines.
Good proficiency practical experience in machine learning generative AI.
Good knowledge of data science tools, libraries, frameworks, platforms such as Python, SQL, AWS (Sagemaker, Bedrock, S3, Glue, Athena), Snowflake, GitHub, PostgreSQL, pgvector, Pandas, NumPy, Scikit‑learn, LangChain, LangGraph, LangFuse, LightRAG.
Ability to write production‑grade code using object‑oriented programming principles.
Ability to design conduct experiments fbuilding well‑performing agentic AI systems evaluating user experience, system bottlenecks, model performance.
Experience developing advanced analytics AI products in a cloud environment delivering valuable analysis through the application of domain business knowledge.
Strong problem‑solving analytical skills.
Strong interpersonal communication skills including active listening, consulting, challenging, presentation skills.
Fluent in English, both written spoken.
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【岗位职责】负责虚拟电厂电力负荷、新能源（光伏风电）出力预测算法的研发、训练与迭代优化，提升预测精度与稳定性。研发储能充放电优化、多源资源协同调度、需求响应邀约等核心算法，支撑虚拟电厂收益*大化。完成电力数据清洗、特征工程、数据集构建，搭建算法模型并完成线上部署、监控与迭代。构建用户用电画像、负荷聚类模型，识别可调负荷潜力，为资源聚合与调度提供数据支撑。研究行业前沿算法与电力市场政策，输出技术方案与创新建议，推动算法与业务深度融合。搭建算法仿真平台，验证调度策略可行性，输出预测、仿真报告，配合业务团队提供技术支持。联合开发团队完成算法工程化落地、封装与系统联调，确保算法适配虚拟电厂业务系统。【任职要求】学历：硕士及以上优先，本科优秀者可放宽；数学、统计学、计算机、人工智能、电气工程、能源动力相关专业。经验：3年及以上电力能源行业算法或数据科学经验，有虚拟电厂、负荷预测、储能调度相关项目经验者优先。算法能力：精通时序预测（、等）、强化学习、运筹优化等算法，熟练使用-、等建模框架。工具技能：熟练使用进行数据处理与建模，精通时序数据库，有大数据处理（）、算法部署经验者优先。业务认知：熟悉虚拟电厂、电力负荷、新能源出力相关业务，了解电力市场、需求响应规则者加分。素养：具备较强的数据洞察与问题解决能力，懂业务落地，沟通协作能力强，能承受项目压力，学习能力突出。加分项：有负荷预测、储能优化项目落地经验；发表过能源相关论文或拥有算法专利；持有相关专业资格证书。