In a world of disruption and increasingly complex business challenges, our professionals bring truth into focus with the Kroll Lens. Our sharp analytical skills, paired with the latest technology, allow us to give our clients clarity—not just answers—in all areas of business. We embrace diverse backgrounds and global perspectives, and we cultivate diversity by respecting, including, and valuing one another. As part of One team, One Kroll, you’ll contribute to a supportive and collaborative work environment that empowers you to excel.

Kroll’s Decision Intelligence Services provides seamless analytical advisory through the deal continuum, from transaction origination to closing.

We are looking for an Analyst with knowledge in data science, strong understanding in Machine Learning and LLM models for Generative AI, text analytics and Python Programming, to scale our Data, Analytics and AI team by developing solutions using data driven techniques and machine learning models.

This, being a core client facing delivery role, offers global exposure of working with other Kroll colleagues, across industries and competencies, with interesting client interactions.

At Kroll, your work will help deliver clarity to our clients’ most complex governance, risk, and transparency challenges. Apply now to join One team, One Kroll.

RESPONSIBILITIES:

• Use scientific methods and advanced techniques to analyse data, obtain insights and develop models and solutions to deliver value to the business.

• Build and implement solutions with AI/GenAI, ML and deep learning (NLP) techniques and develop APIs using Python

• Able to handle large data volumes using most latest techniques and data tools

• Ability to communicate effectively with cross functional teams across regions

• Direct client engagement delivery.

• A strong work initiative, high-energy level, and ability to adapt to new challenges and concepts, including a proactive approach and capacity to perform multiple workstreams and tasks
• A desire and ability to travel while working within the transaction advisory, financial accounting advisory and mergers and acquisition-oriented environment

• Ability to work both independently and as part of a team, including robust communication skills

• Utilizing statistical tools to interpret data sets to identify trends and patterns

• Uphold the firm's code of ethics and business conduct.

REQUIREMENTS:

• 0-6 months of work experience in developing and implementing AI/GenAI, ML models and python programming.

• Well versed with data structure algos, familiarity with different frameworks related to data science, ML, LLM, NLP, tensor flow and similar

• Awareness of MS Azure based deployment with foundational knowledge of Azure Cognitive Services is required

• Experienced in application of statistical techniques like linear and non-linear regressions / classification and optimization areas as well as implementing forecasting models.

• Good to have experience in Merger & Acquisition domain areas like due diligence, deal structuring, financial reporting, value creation and post-merger phases

• Bachelor’s degree in engineering from tier 1 college.

• Experienced in programming, business intelligence (BI) and enterprise resource systems, including data collection, analysis and presentation:

  • Programming languages (Python – must to have)

  • Analytics and data Platforms (AWS, Azure, Snowflake – any one or more of these, preferred Azure)

  • Business Intelligence layer (Power BI, Tableau etc. – good to have)

• Superior analytical and problem-solving skills

• Excellent interpersonal and client relationships skills

• Strong written and verbal communication skills

• Dedication to teamwork

• Proficiency in Microsoft Office, with focus on Word and Excel

• Ability to adapt to ever changing client demands

• Flexibility to travel, as needed.

TECHNICAL Requirements:

• Desire to grow into a techno-functional consultant role

• Able to run business performance management techniques including financial reporting, scenario and optimization models

• Participating in discussions held with Management to determine data analytic needs, data requests and potential impacts on the buy-side/sell-side diligence process, as well as prospective on-going projects

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