Sr Data Scientist

Overview

Develop and deploy machine learning models on large energy datasets

Key Responsibilities

• advanced analytics
• data engineering
• hpc systems
• machine learning
• predictive modeling
• stakeholder training

Tasks

-Educate key stakeholders on the organizations advance analytics capabilities through internal presentations, training workshops, and publications. -Analyze data using advanced analytics techniques in support of process improvement efforts using modern analytics frameworks, including � but not limited to � Python, R, Scala, or equivalent; Spark, Hadoop file system and others (15%) -Access and analyze data sourced from various Company systems of record. Support the development of strategic business, marketing, and program implementation plans. (15%) -Access and enrich data warehouses across multiple Company departments. Build, modify, monitor and maintain high-performance computing systems. (5%) -Support business unit strategic planning while providing a strategic view on machine learning technologies. -Advice and counsel key stakeholders on machine learning findings and recommend courses of action that redirect resources to improve operational performance or assist with overall emerging business issues. -Provide key stakeholders with machine learning analyses that best positions the company going forward. -Provide expert data and analytics support to multiple business units (20%) -Works with stakeholders and subject matter experts to understand business needs, goals and objectives. Work closely with business, engineering, and technology teams to develop solution to data-intensive business problems and translates them into data science projects. Collaborate with other analytic teams across Exelon on big data analytics techniques and tools to improve analytical capabilities. (20%) -Develop key predictive models that lead to delivering a premier customer experience, operating performance improvement, and increased safety best practices. Develop and recommend data sampling techniques, data collections, and data cleaning specifications and approaches. Apply missing data treatments as needed. (25%)

Requirements

• python
• sql
• unix
• machine learning
• masters
• 4-7 years

What You Bring

-Technical Knowledge: Proven experience in developing and deploying predictive analytics projects using one or more leading languages (Python, R, Scala, etc.). Experience working within an open source environment and Unix-based OS. -Analytical Abilities: Strong knowledge in at least two of the following areas: machine learning, artificial intelligence, statistical modeling, data mining, information retrieval, or data visualization. -Experience: Prior exposure to data structures pertaining to smart-meters, billing, or outage management systems. Prior exposure to the utilities or broader energy sector. Prior exposure to the full spectrum of data science lifecycle, including data acquisition, maintenance, processing, analysis, and communication. -Communication Skills: Ability to translate executive and analytics leaders' vision and guidance into methods and analytics. Strong time management and presentation skills. -Analytic Abilities: Solid understanding of relevant theories in machine learning, statistics, probability theory, data structures and algorithms, optimization, etc. -Communication Skills: Ability to translate data analysis and findings into coherent conclusions and actionable recommendations to business partners, practice leaders, and executives. Strong oral and written communication skills. -Education: Bachelor's degree in a Quantitative discipline. Ex: Applied Mathematics, Computer Science, Finance, Operations Research, Physics, Statistics, or related field -Education: Masters, or PhD in a Quantitative discipline. Ex: Applied Mathematics, Computer Science, Finance, Ops Research, Physics, Statistics, Electrical Engineering or related field -Technical Knowledge: Expert level coding skills (Python, R, Scala, SQL, etc), and experience developing in a Unix environment. Proficiency in database management and large datasets: create, edit, update, join, append and query data from columnar and big data platforms. -4-7 years of relevant experience developing hypotheses, applying machine learning algorithms, validating results to analyze multi-terabyte datasets and extracting actionable insights is required. Previous research or professional experience applying advanced analytic techniques to large, complex datasets.

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Benefits

-Annual salary will vary based on a candidate’s skills, qualifications, experience, and other factors: $104,000.00/Yr. – $143,000.00/Yr. -Referral bonus program -401(k) match and annual company contribution -Generous paid time off options, including vacation, sick time, floating and fixed holidays, maternity leave and bonding/primary caregiver leave or parental leave -Employee Assistance Program and resources for mental and emotional support -Medical, dental and vision insurance -Annual Bonus for eligible positions: 15% -Wellbeing programs such as tuition reimbursement, adoption and surrogacy assistance and fitness reimbursement -Life and disability insurance

About Exelon

-Exelon operates as America's largest regulated energy delivery company, formed from the merger of two century-old utilities in 2000. -It focuses on modernizing infrastructure and enhancing grid resilience through continuous investment. -The company's portfolio includes major utilities such as ComEd, BGE, PECO, Pepco, and others, covering vast transmission and distribution systems. -In 2022, Exelon spun off its power generation arm while maintaining full ownership of its transmission and distribution networks. -Exelon’s strategic initiatives often influence the mid-Atlantic and Midwest energy markets, shaping the regional energy landscape.

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